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Sample records for fuzzy topsis approach

  1. Six Sigma Project Selection Using Fuzzy TOPSIS Decision Making Approach

    Directory of Open Access Journals (Sweden)

    Rajeev Rathi

    2015-05-01

    Full Text Available Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.

  2. Equipment Selection by using Fuzzy TOPSIS Method

    Science.gov (United States)

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

  3. Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment

    International Nuclear Information System (INIS)

    Onuet, Semih; Soner, Selin

    2008-01-01

    Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker to describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP

  4. Utilization integrated Fuzzy-QFD and TOPSIS approach in supplier selection

    Directory of Open Access Journals (Sweden)

    2016-02-01

    Full Text Available Supplier selection is a typical multi-attribute problem that involves both qualitative and quantitative factors. To deal with this problem, different techniques have suggested. Being based on purely mathematical data, these techniques have significant drawbacks especially when we want to consider qualitative factors, which are very important in supplier selection and are not easy to measure. Some innovative approaches, based on artificial intelligence techniques such as Fuzzy Logic match very well with decision-making situations especially when decision makers express heterogeneous judgments. In this research, by the combination of Fuzzy logic and the House of Quality (HOQ, qualitative criteria are considered in the forward parts of car suppliers’ selection process in Sazehgostar SAIPA Company. Then, TOPSIS technique is adopted to consider quantitative metrics. Finally, by combining of Fuzzy QFD and TOPSIS techniques, these suppliers will be selected and ranked in this Company. Concern to the both qualitative and quantitative criteria, is the important point used in this research and also methodology utilized, counts innovative aspect. Limited number of experts associated with each piece and unavailability of some quantitative criteria has been limitations across of this study’s accomplishment.

  5. Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Aydin Torkabadi

    2018-03-01

    Full Text Available Purpose: Just-In-Time (JIT production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP, and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.

  6. Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach

    DEFF Research Database (Denmark)

    Rostamzadeh, Reza; Ghorabaee, Mehdi Keshavarz; Govindan, Kannan

    2018-01-01

    Supply chain risk management research has mainly mistreated the important of sustainability issues. Moreover, there is little knowledge about sustainable management of risk and supply chain and the way they impose losses for firms. Risk management's duty in the supply chain is to identify, analyze......, and provide solutions for accountability, control and monitor the risks in the economic and production cycle. This study aims to develop a framework for the sustainable supply chain risk management (SSCRM) evaluation. To this end, an integrated fuzzy multi-criteria decision-making (MCDM) approach is proposed...... based on the technique in order of preference by similarity to ideal solution (TOPSIS) and criteria importance through inter-criteria correlation (CRITIC) methods. The literature was reviewed and the potential criteria were identified. Through an expert panel the criteria were filtered. Seven main...

  7. MULTIPLE CRITERIA DECISION MAKING APPROACH FOR INDUSTRIAL ENGINEER SELECTION USING FUZZY AHP-FUZZY TOPSIS

    OpenAIRE

    Deliktaş, Derya; ÜSTÜN, Özden

    2018-01-01

    In this study, a fuzzy multiple criteria decision-making approach is proposed to select an industrial engineer among ten candidates in a manufacturing environment. The industrial engineer selection problem is a special case of the personal selection problem. This problem, which has hierarchical structure of criteria and many decision makers, contains many criteria. The evaluation process of decision makers also includes ambiguous parameters. The fuzzy AHP is used to determin...

  8. The Application of a Decision-making Approach based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier

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    Rajesri Govindaraju

    2015-09-01

    Full Text Available Supplier selection becomes very important when used in the context of strategic partnerships because of the long-term orientation of the relationship. This paper describes the application of a decision-making approach for selecting a strategic partner (supplier. The approach starts with defining a set of criteria that fits the company’s condition. In the next steps, a combination of fuzzy-ANP and TOPSIS methods is used to determine the weight for each criterion and rank all the alternatives. The application of the approach in an Indonesian manufacturing company showed that the three factors that got the highest weight were “geographical location”, “current operating performance”, and “reliability”. Geographical location got the highest weight because it affects many other factors such as reaction to changes in demand, after-sales service, and delivery lead-time. Application of the approach helps decision-makers to gain effectiveness and efficiency in the decision-making process because it facilitates them to express their group’s collective preferences while also providing opportunities for members to express their individual preferences. Future research can be directed at combining qualitative and quantitative criteria to develop the best criteria and methods for the selection of the best suppliers based on fuzzy ANP and TOPSIS.

  9. A Hybrid Approach Using ISM For Leveling Agile Criteria And Fuzzy AHP To Determine The Relative Weights Of Evaluation Criteria And Fuzzy TOPSIS To Rank The Alternatives

    Directory of Open Access Journals (Sweden)

    Mahdi Karbasian1

    2012-02-01

    Full Text Available In today’s organizations, performance measurement comes more to the foreground with the advancement in the high technology. Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM becomes a useful approach to solve this kind of problem. In order to use the conceptual framework for measuring performance supplier, a methodology that takes into account both quantitative and qualitative factors and the interrelations between them should be utilized. for leveling an integrated approach of analytic hierarchy process AHP and fuzzy TOPSIS method is proposed to obtain final ranking. The interactions among the criteria are also analyzed before arriving at a decision for the selection of supplier from among six alternatives. Linguistic values are used to assess the ratings and weights for criterion. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM model based on fuzzy-sets theory including FAHP and FTOPSIS are applied. There are two approaches for aggregating values including relative importance of evaluation criteria with respect to the overall objective and rating of alternatives with respect to each criterion in fuzzy group TOPSIS: First aggregation and Last aggregation. In first aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are aggregated at first and TOPSIS method then apply to these aggregate values. In last aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are used in TOPSIS method

  10. Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study

    OpenAIRE

    Yashon O. Ouma; J. Opudo; S. Nyambenya

    2015-01-01

    For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS) is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pa...

  11. Assessing Sustainable Rural Community Tourism Using the AHP and TOPSIS Approaches under Fuzzy Environment

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    Mujiya Ulkhaq M.

    2016-01-01

    Full Text Available Tourism is currently a sector that is growing into an important and significant world activity. The development of an area where the tourist destination located in affects the growth of the tourism. In addition, the success of tourist destinations are influenced by their relative competitiveness; hence, they do compete each other to offer the best service to satisfy their customers. Rural tourism in Indonesia is believed as emerging business since there are abundant sites located in rural area that offers fascinating attractions to the visitors. This study aims to evaluate the rural tourism using sustainable indicators, namely, service quality, facilities, management system, and outcome. A combination of fuzzy AHP and TOPSIS are employed to select five rural tourism in Central Java Province. Result shows that service quality is considered as the most important attribute with weight of 28.6%, while Dieng is named for the excellent rural tourism. This finding might offer the service providers with valuable insights into the attribute that reflects customers’ perceptions about rural tourism; also to position their services based on their competitors.

  12. Evaluating Emergency Response Solutions for Sustainable Community Development by Using Fuzzy Multi-Criteria Group Decision Making Approaches: IVDHF-TOPSIS and IVDHF-VIKOR

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    Junling Zhang

    2016-03-01

    Full Text Available Emergency management is vital in implementing sustainable community development, for which community planning must include emergency response solutions to potential natural and manmade hazards. To help maintain such solution repository, we investigate effective fuzzy multi-criteria group decision making (FMCGDM approaches for the complex problems of evaluating alternative emergency response solutions, where weights for decision makers and criteria are unknown due to problem complexity. We employ interval-valued dual hesitant fuzzy (IVDHF set to address decision hesitancy more effectively. Based on IVDHF assessments, we develop a deviation maximizing model to compute criteria weights and another compatibility maximizing model to calculate weights for decision makers. Then, two ideal-solution-based FMCGDM approaches are proposed: (i by introducing a synthesized IVDHF group decision matrix into TOPSIS, we develop an IVDHF-TOPSIS approach for fuzzy group settings; (ii when emphasizing both maximum group utility and minimum individual regret, we extend VIKOR to develop an IVDHF-VIKOR approach, where the derived decision makers’ weights are utilized to obtain group decision matrix and the determined criteria weights are integrated to reflect the relative importance of distances from the compromised ideal solution. Compared with aggregation-operators-based approach, IVDHF-TOPSIS and IVDHF-VIKOR can alleviate information loss and computational complexity. Numerical examples have validated the effectiveness of the proposed approaches.

  13. Investigating Rate of Iatric Tourisms’ Satisfaction and Prioritizing the Effective Factors on it via Fuzzy TOPSIS Approach

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    M Sadr Bafghi

    2013-01-01

    Full Text Available Introduction: This research aimed to investigate rate of iatric tourisms’ satisfaction about provided medical services for them and their fellow travelers in Yazd city. For this purpose, the quality level of services provided to the patients and their fellow travelers was investigated and some solutions have been suggested in order to enhance this level. Methods: In this direction, a questionnaire was designed according to SERVQUAL model in 5 aspects consisting of 21 questions. Therefore, quality differences have been measured according to opinions of 114 foreign patients and their fellow travelers in the hospitals around the city. This is a descriptive- measurement research. In order to analyze the data available techniques in statistics were utilized and Fuzzy TOPSIS technique was used for prioritizing the solutions. Results: The results revealed that services quality difference is significant in 3 aspects of responsibility, guarantee and agreement. In other words, there is a significant difference between patients’ perception and expectation with those of their fellow travelers regarding quality of provided services. Conclusion: However, results of rating with Fuzzy TOPSIS indicated that the factors of proper equipments and proper quality of therapy are in the better situation comparing with other factors.

  14. A novel framework of ERP implementation in Indian SMEs: Kernel principal component analysis and intuitionistic Fuzzy TOPSIS driven approach

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    Indranil Ghosh

    2016-04-01

    Full Text Available Over the years, organizations have witnessed a transformational change at global market place. Integration of operations and partnership have become the key success factors for organizations. In order to achieve inclusive growth while operating in a dynamic uncertain environment, organizations irrespective of the scale of business need to stay connected across the entire value chain. The purpose of this paper is to analyze Enterprise Resource Planning (ERP implementation process for Small and Medium Enterprises (SMEs in India to identify the key enablers. Exhaustive survey of existing literature as a part of secondary research work, has been conducted in order to identify the critical success factors and usefulness of ERP implementation in different industrial sectors initially and examines the impact of those factors in Indian SMEs. Kernel Principal Component Analysis (KPCA has been applied on survey response to recognize the key constructs related to Critical Success Factors (CSFs and tangible benefits of ERP implementation. Intuitionistic Fuzzy set theory based Technique of Order Preference by Similarity to Ideal Solution (TOPSIS method is then used to rank the respective CSFs by mapping their contribution to the benefits realized through implementing ERP. Overall this work attempts to present a guideline for ERP adoption process in the said sector utilizing the framework built upon KPCA and Intuitionistic Fuzzy TOPSIS. Findings of this work can act as guidelines for monitoring the entire ERP implementation project.

  15. Integrated AHP Intuitionistic Fuzzy Topsis

    African Journals Online (AJOL)

    It is concluded that adopting scientific approach to humanistic system is appropriate ... to bring about accuracy and effective ranking of alternatives. By so doing, eliminating ..... performance evaluation of telecommunication company. American ...

  16. Assessing intellectual capital management by fuzzy TOPSIS

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    Hossein Jannatifar

    2012-10-01

    Full Text Available Intellectual capital is a type of asset measuring ability of economic agency in order tomake wealth. These assets do not have physical and objective nature and are intangible assets being achieved through utilization of relative assets with human resources, organizational operation and foreign relations from economic agency. Measuring this issue is important from intra-organizational and extra-organizational views. In this paper, we present survey based on Fuzzy TOPSIS to find important factors influencing intellectual capital management. The proposed model of this paper considers different factors, which exist in the literature and prioritize them based on different criteria. The results of our survey identified seven items as the most influencing factors.

  17. Application of Fuzzy TOPSIS MADM approach in ranking & underlining the problems of plywood industry in India

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    Kapil Mittal

    2016-12-01

    Full Text Available The manufacturing of plywood consists of simple procedural steps, but the range of problems associated with the plywood manufacturing industries, especially in the case of small-scale industries (SSI, is large. This paper describes the major problems faced by the plywood SSIs along with their cause and the ultimate effect, i.e. pruning the profits. Many cogent tools and techniques are present for the task, but an attempt has been made to apply multiple attribute decision-making (MADM approach in ranking the problems in order of their extent on the basis of various parameters. Some suggestions for the improvement purposes have also been made to overcome the top-ranked problem. The study is the first of its type in a plywood industry, although same can be applied to other similar small-scale cluster industries like steel, textile, pharmaceutical, and automobile.

  18. COMPARATIVE ANALYSIS OF TOPSIS AND FUZZY TOPSIS FOR THE EVALUATION OF TRAVEL WEBSITE SERVICE QUALITY

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    Golam Kabir

    2012-09-01

    Full Text Available The Internet revolution has led to significant changes in the way travel agencies interact with customers. Travel websites provide customers diverse services including travel information and products through the Internet. In practical envir onments, Internet users face a variety of travel website service quality (TWSQ that is vague from human beings' subjective judgments, and most criteria have some degree of interdependent or interactive characteristics. In the face of the strong competitio n environment, in order to profit by making customers proceed with transactions on the websites, travel websites should pay more attention to improve their service quality. This study discusses the major factors for travel agency websites quality from the viewpoint of users' perception and explores the use of multiple - attribute decision making (MADM approaches for the evaluation of TWSQ. A comparative analysis of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS and Fuzzy TOPSIS metho ds are illustrated through a practical application from the websites of five travel agencies. Empirical results showed that the proposed methods are viable approaches in solving the evaluation problem of TWSQ.

  19. Implementasi Metode Fuzzy TOPSIS untuk Seleksi Penerimaan Karyawan

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    Sri Lestari

    2011-07-01

    Full Text Available Abstract —An emerging institution would continue to need qualified workers to produce good performances.  Seeing the importance of high quality employees, the candidate selection process became an important part and should be performed promptly.  It is also important to have candidates with desirable criteria fit to the institution. Many proposed methods can be adapted to help employee selection process based on criteria.  This research propose an employee selection system based on Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS method, because the proposed method capable to deal with multi dimensional problems in employees selection.  The system will produce ranks that can be used to help the hiring decision. This research also compares the results from TOPSIS method and WPM method.  The comparison result shows that both methods produce the same ranks for the chosen candidates. Keywords—  Fuzzy TOPSIS, WPM, Employee Selection.

  20. Penerapan Fuzzy Topsis Untuk Seleksi Penerima Bantuan Kemiskinan

    OpenAIRE

    Sukerti, Ni Kadek

    2015-01-01

    Some factors that cause mis target of poor relief are inacurate criteria of poor citizen as well as inexactly method that make error in manual calculation. Fuzzy Technique for Order Preference by Similarity to Ideal Solution Method (Fuzzy TOPSIS) is used to select the receiver of poor relief in order to make alternative ranking to compare. It's implementation is by using excel and matlab with ten alternative (village) which is will compare based on their criteria and subcriteria. The criteria...

  1. National hydrogen technology competitiveness analysis with an integrated fuzzy AHP and TOPSIS approaches: In case of hydrogen production and storage technologies

    Science.gov (United States)

    Lee, Seongkon; Mogi, Gento

    2017-02-01

    The demand of fossil fuels, including oil, gas, and coal has been increasing with the rapid development of developing countries such as China and India. U.S., Japan, EU, and Korea have been making efforts to transfer to low carbon and green growth economics for sustainable development. And they also have been measuring to cope with climate change and the depletion of conventional fuels. Advanced nations implemented strategic energy technology development plans to lead the future energy market. Strategic energy technology development is crucial alternative to address the energy issues. This paper analyze the relative competitiveness of hydrogen energy technologies in case of hydrogen production and storage technologies from 2006 to 2010. Hydrogen energy technology is environmentally clean technology comparing with the previous conventional energy technologies and will play a key role to solve the greenhouse gas effect. Leading nations have increasingly focused on hydrogen technology R&D. This research is carried out the relative competitiveness of hydrogen energy technologies employed by an integrated fuzzy analytic hierarchy process (Fuzzy AHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches. We make four criteria, accounting for technological status, R&D budget, R&D human resource, and hydrogen infra. This research can be used as fundamental data for implementing national hydrogen energy R&D planning for energy policy-makers.

  2. Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study

    Directory of Open Access Journals (Sweden)

    Yashon O. Ouma

    2015-01-01

    Full Text Available For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pavement conditions for automated maintenance prioritization. From the case study results, four pavement maintenance objectives were determined as road safety, pavement surface preservation, road operational status and standards, and road aesthetics, with corresponding depreciating significance weights of W=0.37,0.31,0.22,0.10T. The top three maintenance functions were identified as Thin Hot Mix Asphalt (HMA overlays, resurfacing and slurry seals, which were a result of pavement cracking, potholes, raveling, and patching, while the bottom three were cape seal, micro surfacing, and fog seal. The two methods gave nearly the same prioritization ranking. In general, the fuzzy AHP approach tended to overestimate the maintenance prioritization ranking as compared to the fuzzy TOPSIS.

  3. Evaluation of Combined Heat and Power (CHP Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

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    Fausto Cavallaro

    2016-06-01

    Full Text Available Combined heat and power (CHP or cogeneration can play a strategic role in addressing environmental issues and climate change. CHP systems require less fuel than separate heat and power systems in order to produce the same amount of energy saving primary energy, improving the security of the supply. Because less fuel is combusted, greenhouse gas emissions and other air pollutants are reduced. If we are to consider the CHP system as “sustainable”, we must include in its assessment not only energetic performance but also environmental and economic aspects, presenting a multicriteria issue. The purpose of the paper is to apply a fuzzy multicriteria methodology to the assessment of five CHP commercial technologies. Specifically, the combination of the fuzzy Shannon’s entropy and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS approach will be tested for this purpose. Shannon’s entropy concept, using interval data such as the α-cut, is a particularly suitable technique for assigning weights to criteria—it does not require a decision-making (DM to assign a weight to the criteria. To rank the proposed alternatives, a fuzzy TOPSIS method has been applied. It is based on the principle that the chosen alternative should be as close as possible to the positive ideal solution and be as far as possible from the negative ideal solution. The proposed approach provides a useful technical–scientific decision-making tool that can effectively support, in a consistent and transparent way, the assessment of various CHP technologies from a sustainable point of view.

  4. Measuring the Leanness of Manufacturing system Using Fuzzy TOPSIS : A Case Study of Parizan Sanat Company

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    Akram, Rasoul

    2013-11-01

    Full Text Available The implementation of lean manufacturing concepts has had a significant impact on various industries. Many companies around the world have attempted to implement lean manufacturing, but the lack of an obvious understanding of lean measurement and its performance has caused its implementation to fail. This paper presents an innovative approach by using fuzzy TOPSIS to measure the production leanness of manufacturing systems, as a paradigm. This approach is applied to the Parizan Sanat company.

  5. Application of Intuitionistic Fuzzy Topsis Model for Troubleshooting an Offshore Patrol Boat Engine

    Directory of Open Access Journals (Sweden)

    Aikhuele Daniel Osezua

    2017-06-01

    Full Text Available In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert’s opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failures are easily detected using expert’s based opinions.

  6. A triangular fuzzy TOPSIS-based approach for the application of water technologies in different emergency water supply scenarios.

    Science.gov (United States)

    Qu, Jianhua; Meng, Xianlin; Yu, Huan; You, Hong

    2016-09-01

    Because of the increasing frequency and intensity of unexpected natural disasters, providing safe drinking water for the affected population following a disaster has become a global challenge of growing concern. An onsite water supply technology that is portable, mobile, or modular is a more suitable and sustainable solution for the victims than transporting bottled water. In recent years, various water techniques, such as membrane-assisted technologies, have been proposed and successfully implemented in many places. Given the diversity of techniques available, the current challenge is how to scientifically identify the optimum options for different disaster scenarios. Hence, a fuzzy triangular-based multi-criteria, group decision-making tool was developed in this research. The approach was then applied to the selection of the most appropriate water technologies corresponding to the different emergency water supply scenarios. The results show this tool capable of facilitating scientific analysis in the evaluation and selection of emergency water technologies for enduring security drinking water supply in disaster relief.

  7. Optimal Partner Combination for Joint Distribution Alliance using Integrated Fuzzy EW-AHP and TOPSIS for Online Shopping

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    Yandong He

    2016-04-01

    Full Text Available With the globalization of online shopping, deterioration of the ecological environment and the increasing pressure of urban transportation, a novel logistics service mode—joint distribution (JD—was developed. Selecting the optimal partner combination is important to ensure the joint distribution alliance (JDA is sustainable and stable, taking into consideration conflicting criteria. In this paper, we present an integrated fuzzy entropy weight, fuzzy analytic hierarchy process (fuzzy EW-AHP and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS approach to select the optimal partner combination of JDA. A three-phase approach is proposed. In the first phase, we identify partner combination evaluation criteria using an economy-society-environment-flexibility (ESEF framework from a perspective that considers sustainability. In the second phase, the criteria weights and criteria combination performance of different partner combinations were calculated by using an integrated fuzzy EW-AHP approach considering the objective and subjective factors of experts. In the third phase, the JDA partner combinations are ranked by employing fuzzy TOPSIS approach. The sensitivity analysis is considered for the optimal partner combination. Taking JDA in Chongqing for example, the results indicate the alternative partner combination 3 (PC3 is always ranked first no matter how the criteria weights change. It is effective and robust to apply the integrated fuzzy EW-AHP and TOPSIS approach to the partner selection of JDA.

  8. SMART Grid Evaluation Using Fuzzy Numbers and TOPSIS

    Science.gov (United States)

    El Alaoui, Mohammed

    2018-05-01

    In recent advent of smart grids, the end-users aims to satisfy simultaneously low electricity bills, with a reasonable level of comfort. While cost evaluation appears to be an easy task, capturing human preferences seems to be more challenging. Here we propose the use of fuzzy logic and a modified version of the TOPSIS method, to quantify end-users’ preferences in a smart grid. While classical smart grid focus only on the technological side, it is proven that smart grid effectiveness is hugely linked to end-users’ behaviours. The main objective here, is to involve smart grid users in order to get maximum satisfaction, preserving classical smart grid objectives.

  9. Personel Seçiminde Çok Kriterli Karar Verme: Bulanık Topsis Uygulaması - Multi-Criteria Approach to Personnel Selection: Fuzzy Topsis Applications

    Directory of Open Access Journals (Sweden)

    Nalan Gülten AKIN

    2016-06-01

    Full Text Available Which are very important in terms of human resource management, personnel selection, it expressed as a process of determining the appropriate personnel hired to perform the work. Personnel selection, often occurs as a result of decisions made by a group decision based on the evaluation of candidates by various criteria and subjective judgment transmitter. Whereas the organization that they can gain competitive advantage and this advantage can continue, according to the right personnel for the right job it depends on the objective criteria chosen. Personnel selection problems, decision-making and be more than the number of candidates and the terms of a number of criteria involved in the decision to take effect on multi-criteria decision problems. Decisions based on personal jurisdiction includes the uncertainty. Therefore, one of the multiple-criteria decision analysis techniques in this study preferred method of fuzzy TOPSIS. In the process of recruiting a research assistant in a public university under study, which will be invited to the scientific examination of the candidates who apply, with proximity to the ranking made by calculating the coefficients for each candidate is determined based on objective criteria

  10. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    Science.gov (United States)

    Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

    2017-12-01

    There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

  11. A Voting TOPSIS Approach for Determining the Priorities of Areas Damaged in Disasters

    Directory of Open Access Journals (Sweden)

    Yanjin He

    2018-05-01

    Full Text Available In this paper, we investigate the priority determination problem for areas that have been damaged during disasters. Relief distribution should be planned while considering the priorities of the damaged areas. To determine the priorities of the damaged areas, we first define four criteria and then propose a voting TOPSIS (technique for order of preference by similarity to ideal solution that utilizes the fuzzy pair-wise comparison, data envelopment analysis, and TOPSIS. Since the voting TOPSIS is based on the voting results of multiple experts, it can be applied to urgent situations quickly, regardless of the consistency of comparison, the number of alternatives, and the number of participating experts. The proposed approach is validated using a real-world case, and this case analysis shows that the voting TOPSIS is viable.

  12. THIRD PARTY LOGISTIC SERVICE PROVIDER SELECTION USING FUZZY AHP AND TOPSIS METHOD

    Directory of Open Access Journals (Sweden)

    Golam Kabir

    2012-03-01

    Full Text Available The use of third party logistic(3PL services providers is increasing globally to accomplish the strategic objectives. In the increasingly competitive environment, logistics strategic management requires systematic and structured approach to have cutting edge over the rival. Logistics service provider selection is a complex multi-criteria decision making process; in which, decision makers have to deals with the optimization of conflicting objectives such as quality, cost, and delivery time. In this paper, fuzzy analytic hierarchy process (FAHP approach based on technique for order preference by similarity to ideal solution (TOPSIS method has been proposed for evaluating and selecting an appropriate logistics service provider, where the ratings of each alternative and importance weight of each criterion are expressed in triangular fuzzy numbers.

  13. Framework for benchmarking online retailing performance using fuzzy AHP and TOPSIS method

    Directory of Open Access Journals (Sweden)

    M. Ahsan Akhtar Hasin

    2012-08-01

    Full Text Available Due to increasing penetration of internet connectivity, on-line retail is growing from the pioneer phase to increasing integration within people's lives and companies' normal business practices. In the increasingly competitive environment, on-line retail service providers require systematic and structured approach to have cutting edge over the rival. Thus, the use of benchmarking has become indispensable to accomplish superior performance to support the on-line retail service providers. This paper uses the fuzzy analytic hierarchy process (FAHP approach to support a generic on-line retail benchmarking process. Critical success factors for on-line retail service have been identified from a structured questionnaire and literature and prioritized using fuzzy AHP. Using these critical success factors, performance levels of the ORENET an on-line retail service provider is benchmarked along with four other on-line service providers using TOPSIS method. Based on the benchmark, their relative ranking has also been illustrated.

  14. Prioritizing critical success factors for reverse logistics implementation using fuzzy-TOPSIS methodology

    Science.gov (United States)

    Agrawal, Saurabh; Singh, Rajesh K.; Murtaza, Qasim

    2016-03-01

    Electronics industry is one of the fastest growing industries in the world. In India also, there are high turnovers and growing demand of electronics product especially after post liberalization in early nineties. These products generate e-waste which has become big environmental issue. Industries can handle these e-waste and product returns efficiently by developing reverse logistics (RL) system. A thorough study of critical success factors (CSFs) and their ordered implementation is essential for successful RL implementation. The aim of the study is to review the CSFs, and to prioritize them for RL implementation in Indian electronics industry. Twelve CSFs were identified through literature review, and discussion with the experts from the Indian electronics industry. Fuzzy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach is proposed for prioritizing these CSFs. Perusal of literature indicates that fuzzy-TOPSIS has not been applied earlier for prioritization of CSFs in Indian electronics industry. Five Indian electronics companies were selected for evaluation of this methodology. Results indicate that most of the identified factors are crucial for the RL implementation. Top management awareness, resource management, economic factors, and contracts terms and conditions are top four prioritized factor, and process capabilities and skilled workers is the least prioritized factor. The findings will be useful for successful RL implementation in Indian electronics industry.

  15. Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

    Science.gov (United States)

    Irvanizam, I.

    2018-03-01

    Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

  16. The fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for nuclear power plant site selection - a case study from Turkey

    International Nuclear Information System (INIS)

    Kurt, Ünal

    2014-01-01

    The location selection for nuclear power plant (NPP) is a strategic decision, which has significant impact on the economic operation of the plant and sustainable development of the region. This paper proposes fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for evaluation and selection of optimal locations for NPP in Turkey. Many sub-criteria such as geological, social, touristic, transportation abilities, cooling water capacity and nearest to consumptions markets are taken into account. Among the evaluated locations, according to generalized Choquet fuzzy integral method, Inceburun–Sinop was selected as a study site due to its highest performance and meeting most of the investigated criteria. The Inceburun-Sinop is selected by generalized Choquet fuzzy integral and fuzzy TOPSIS Iğneada–Kırklareli took place in the first turn. The Mersin–Akkuyu is not selected in both methods. (author)

  17. A New Hesitant Fuzzy Linguistic TOPSIS Method for Group Multi-Criteria Linguistic Decision Making

    Directory of Open Access Journals (Sweden)

    Fangling Ren

    2017-11-01

    Full Text Available Hesitant fuzzy linguistic decision making is a focus point in linguistic decision making, in which the main method is based on preference ordering. This paper develops a new hesitant fuzzy linguistic TOPSIS method for group multi-criteria linguistic decision making; the method is inspired by the TOPSIS method and the preference degree between two hesitant fuzzy linguistic term sets (HFLTSs. To this end, we first use the preference degree to define a pseudo-distance between two HFLTSs and analyze its properties. Then we present the positive (optimistic and negative (pessimistic information of each criterion provided by each decision maker and aggregate these by using weights of decision makers to obtain the hesitant fuzzy linguistic positive and negative ideal solutions. On the basis of the proposed pseudo-distance, we finally obtain the positive (negative ideal separation matrix and a new relative closeness degree to rank alternatives. We also design an algorithm based on the provided method to carry out hesitant fuzzy linguistic decision making. An illustrative example shows the elaboration of the proposed method and comparison with the symbolic aggregation-based method, the hesitant fuzzy linguistic TOPSIS method and the hesitant fuzzy linguistic VIKOR method; it seems that the proposed method is a useful and alternative decision-making method.

  18. A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems

    Directory of Open Access Journals (Sweden)

    Ghazanfari Mehdi

    2014-04-01

    Full Text Available Evaluation of the Business Intelligence (BI competencies of port community systems before they are bought and deployed is a vital importance for establishment of a decision-support environment for managers. This study proposes a new model which provides a simple approach to the assessment of the BI competencies of port community systems in organization. This approach helps decision-makers to select an enterprise system with appropriate intelligence requirements to support the managers’ decision-making tasks. Thirtyfour criteria for BI specifications are determined from a thorough review of the literature. The proposed model uses the fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of port community systems to compute the evaluation scores and rankings. The application of the model is realized in the evaluation, ranking and selecting of the needed port community systems in a port and maritime organization, in order to validate the proposed model with a real application. With utilizing the proposed model organizations can assess, select, and purchase port community systems which will provide a better decision-support environment for their business systems.

  19. Project portfolio selection of banking services using COPRAS and Fuzzy-TOPSIS

    Directory of Open Access Journals (Sweden)

    C.O. Anyaeche

    2017-04-01

    Full Text Available Portfolio selection is a business process which has helped organisations identify an area of com-petitive advantage and it is a major concern to industrial players in the banking sectors. In order to enhance bank portfolio selection, cost, profitability, time and location are important parameters that decision-makers often consider. This study implements a fuzzy-TOPSIS (Technique for Or-der Preference by Similarity to Ideal Solution framework to evaluate three potential portfolios (automated teller machine gallery, quick service point and branch for a bank using the infor-mation from three decision-makers. An illustrative example of real bank information is used to demonstrate the proposed framework applicability. The complex proportional assessment of al-ternatives (COPRAS method is also used as an evaluation technique and the results are com-pared, which yields that the results from the ranking order of fuzzy-TOPSIS and COPRAS were different. However, there is a consistency between the aggregation of intuition-based, fuzzy-TOPSIS and COPRAS ranks and fuzzy-TOPSIS ranking results. The presented framework is an easy-to-apply tool that improves portfolio selection decision in the banking system.

  20. Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

    Science.gov (United States)

    Yazdi, Mohammad; Korhan, Orhan; Daneshvar, Sahand

    2018-05-09

    This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event. To find the probability of the top event (TE), all probabilities of the basic events (BEs) should be available when the FTA is drawn. In this case, employing expert judgment can be used as an alternative to failure data in an awkward situation. The fuzzy analytical hierarchy process as a standard technique is used to give a specific weight to each expert, and fuzzy set theory is engaged for aggregating expert opinion. In this regard, the probability of BEs will be computed and, consequently, the probability of the TE obtained using Boolean algebra. Additionally, to reduce the probability of the TE in terms of three parameters (safety consequences, cost and benefit), the importance measurement technique and modified TOPSIS was employed. The effectiveness of the proposed approach is demonstrated with a real-life case study.

  1. Application of Fuzzy TOPSIS for evaluating machining techniques using sustainability metrics

    Science.gov (United States)

    Digalwar, Abhijeet K.

    2018-04-01

    Sustainable processes and techniques are getting increased attention over the last few decades due to rising concerns over the environment, improved focus on productivity and stringency in environmental as well as occupational health and safety norms. The present work analyzes the research on sustainable machining techniques and identifies techniques and parameters on which sustainability of a process is evaluated. Based on the analysis these parameters are then adopted as criteria’s to evaluate different sustainable machining techniques such as Cryogenic Machining, Dry Machining, Minimum Quantity Lubrication (MQL) and High Pressure Jet Assisted Machining (HPJAM) using a fuzzy TOPSIS framework. In order to facilitate easy arithmetic, the linguistic variables represented by fuzzy numbers are transformed into crisp numbers based on graded mean representation. Cryogenic machining was found to be the best alternative sustainable technique as per the fuzzy TOPSIS framework adopted. The paper provides a method to deal with multi criteria decision making problems in a complex and linguistic environment.

  2. Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks.

    Science.gov (United States)

    Chiu, Ming-Chuan; Hsieh, Min-Chih

    2016-05-01

    The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  3. Decision Making in Uncertain Rural Scenarios by means of Fuzzy TOPSIS Method

    Directory of Open Access Journals (Sweden)

    Eva Armero

    2011-01-01

    Full Text Available A great deal of uncertain information which is difficult to quantify is taken into account by farmers and experts in the enterprise when making decisions. We are interested in the problems of the implementation of a rabbit-breeding farm. One of the first decisions to be taken refers to the design or type of structure for housing the animals, which is determined by the level of environmental control sought to be maintained in its interior. A farmer was consulted, and his answers were incorporated into the analysis, by means of the fuzzy TOPSIS methodology. The main purpose of this paper is to study the problem by means of the fuzzy TOPSIS method as multicriteria decision making, when the information was given in linguistic terms.

  4. Penerapan Metode AHP dan Fuzzy Topsis Untuk Sistem Pendukung Keputusan Promosi Jabatan

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    Ari Muhardono

    2016-01-01

    Full Text Available Resources of humans is one of the assets of the organization that became the backbone of an organization in carrying out its activities and influence on the performance and progress of the organization. Systematic performance assessment and selection of employees with the best performance for the determination of a promotion is very important in strategic human resource management. But in fact the decision objectively, efficiently and effectively perform the selection of human resources is not easy, we need a model of decision-making to help solve that problem. Application of AHP and Fuzzy TOPSIS in the selection of this promotion can be provide alternative recommendations for decision-makers, so that the employee selection process can take place effectively and efficiently and to produce objective decisions. Implementation results of the study for the selection of a promotion with six criteria assessment criteria weighting the results obtained using the AHP Performance Value of 0,3509, Education Level of 0,1605, Class of 0,1005, Work period of 0,0367, The Presence of 0,0637 and the value of the competence of 0.2877. The weighting of the results was continued process of ranking the alternatives by using fuzzy TOPSIS method obtained the best results and the selected preference is for 0.8373   Keywords: Performance evaluation; Promotion; AHP; Topsis; Fuzzy

  5. A YinYang bipolar fuzzy cognitive TOPSIS method to bipolar disorder diagnosis.

    Science.gov (United States)

    Han, Ying; Lu, Zhenyu; Du, Zhenguang; Luo, Qi; Chen, Sheng

    2018-05-01

    Bipolar disorder is often mis-diagnosed as unipolar depression in the clinical diagnosis. The main reason is that, different from other diseases, bipolarity is the norm rather than exception in bipolar disorder diagnosis. YinYang bipolar fuzzy set captures bipolarity and has been successfully used to construct a unified inference mathematical modeling method to bipolar disorder clinical diagnosis. Nevertheless, symptoms and their interrelationships are not considered in the existing method, circumventing its ability to describe complexity of bipolar disorder. Thus, in this paper, a YinYang bipolar fuzzy multi-criteria group decision making method to bipolar disorder clinical diagnosis is developed. Comparing with the existing method, the new one is more comprehensive. The merits of the new method are listed as follows: First of all, multi-criteria group decision making method is introduced into bipolar disorder diagnosis for considering different symptoms and multiple doctors' opinions. Secondly, the discreet diagnosis principle is adopted by the revised TOPSIS method. Last but not the least, YinYang bipolar fuzzy cognitive map is provided for the understanding of interrelations among symptoms. The illustrated case demonstrates the feasibility, validity, and necessity of the theoretical results obtained. Moreover, the comparison analysis demonstrates that the diagnosis result is more accurate, when interrelations about symptoms are considered in the proposed method. In a conclusion, the main contribution of this paper is to provide a comprehensive mathematical approach to improve the accuracy of bipolar disorder clinical diagnosis, in which both bipolarity and complexity are considered. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Novel Distance Measure in Fuzzy TOPSIS for Supply Chain Strategy Based Supplier Selection

    Directory of Open Access Journals (Sweden)

    B. Pardha Saradhi

    2016-01-01

    Full Text Available In today’s highly competitive environment, organizations need to evaluate and select suppliers based on their manufacturing strategy. Identification of supply chain strategy of the organization, determination of decision criteria, and methods of supplier selection are appearing to be the most important components in research area in the field of supply chain management. In this paper, evaluation of suppliers is done based on the balanced scorecard framework using new distance measure in fuzzy TOPSIS by considering the supply chain strategy of the manufacturing organization. To take care of vagueness in decision making, trapezoidal fuzzy number is assumed for pairwise comparisons to determine relative weights of perspectives and criteria of supplier selection. Also, linguistic variables specified in terms of trapezoidal fuzzy number are considered for the payoff values of criteria of the suppliers. These fuzzy numbers satisfied the Jensen based inequality. A detailed application of the proposed methodology is illustrated.

  7. Evaluation of B2C website based on the usability factors by using fuzzy AHP & hierarchical fuzzy TOPSIS

    Science.gov (United States)

    Masudin, I.; Saputro, T. E.

    2016-02-01

    In today's technology, electronic trading transaction via internet has been utilized properly with rapid growth. This paper intends to evaluate related to B2C e-commerce website in order to find out the one which meets the usability factors better than another. The influential factors to B2C e-commerce website are determined for two big retailer websites. The factors are investigated based on the consideration of several studies and conformed to the website characteristics. The evaluation is conducted by using different methods namely fuzzy AHP and hierarchical fuzzy TOPSIS so that the final evaluation can be compared. Fuzzy triangular number is adopted to deal with imprecise judgment under fuzzy environment.

  8. Rough Set Theory Based Fuzzy TOPSIS on Serious Game Design Evaluation Framework

    Directory of Open Access Journals (Sweden)

    Chung-Ho Su

    2013-01-01

    Full Text Available This study presents a hybrid methodology for solving the serious game design evaluation in which evaluation criteria are based on meaningful learning, ARCS motivation, cognitive load, and flow theory (MACF by rough set theory (RST and experts’ selection. The purpose of this study tends to develop an evaluation model with RST based fuzzy Delphi-AHP-TOPSIS for MACF characteristics. Fuzzy Delphi method is utilized for selecting the evaluation criteria, Fuzzy AHP is used for analyzing the criteria structure and determining the evaluation weight of criteria, and Fuzzy TOPSIS is applied to determine the sequence of the evaluations. A real case is also used for evaluating the selection of MACF criteria design for four serious games, and both the practice and evaluation of the case could be explained. The results show that the playfulness (C24, skills (C22, attention (C11, and personalized (C35 are determined as the four most important criteria in the MACF selection process. And evaluation results of case study point out that Game 1 has the best score overall (Game 1 > Game 3 > Game 2 > Game 4. Finally, proposed evaluation framework tends to evaluate the effectiveness and the feasibility of the evaluation model and provide design criteria for relevant multimedia game design educators.

  9. Human health and safety risks management in underground coal mines using fuzzy TOPSIS

    Energy Technology Data Exchange (ETDEWEB)

    Mahdevari, Satar, E-mail: satar.mahdevari@aut.ac.ir [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Shahriar, Kourosh [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Esfahanipour, Akbar [Industrial Engineering Department, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

    2014-08-01

    The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

  10. Human health and safety risks management in underground coal mines using fuzzy TOPSIS

    International Nuclear Information System (INIS)

    Mahdevari, Satar; Shahriar, Kourosh; Esfahanipour, Akbar

    2014-01-01

    The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

  11. Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment

    OpenAIRE

    S. Rahmani; M. Omidvari

    2016-01-01

    Introduction: Electrical industries are among high risk industries. The present study aimed to assess safety risk in electricity distribution processes using  ET&BA technique and also to compare with both VIKOR & TOPSIS methods in fuzzy environments.   Material and Methods: The present research is a descriptive study and ET&BA worksheet is the main data collection tool. Both Fuzzy TOPSIS and Fuzzy VIKOR methods were used for the worksheet analysis.   Result: Findi...

  12. Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2016-01-01

    Full Text Available As an efficient way to deal with the global climate change and energy shortage problems, a strong, self-healing, compatible, economic and integrative smart gird is under construction in China, which is supported by large amounts of investments and advanced technologies. To promote the construction, operation and sustainable development of Strong Smart Grid (SSG, a novel hybrid framework for evaluating the performance of SSG is proposed from the perspective of sustainability. Based on a literature review, experts’ opinions and the technical characteristics of SSG, the evaluation model involves four sustainability criteria defined as economy, society, environment and technology aspects associated with 12 sub-criteria. Considering the ambiguity and vagueness of the subjective judgments on sub-criteria, fuzzy TOPSIS method is employed to evaluate the performance of SSG. In addition, different from previous research, this paper adopts the stochastic Analytical Hierarchy Process (AHP method to upgrade the traditional Technique for Order Preference by Similarity to Ideal Solution (TOPSIS by addressing the fuzzy and stochastic factors within weights calculation. Finally, four regional smart grids in China are ranked by employing the proposed framework. The results show that the sub-criteria affiliated with environment obtain much more attention than that of economy from experts group. Moreover, the sensitivity analysis indicates the ranking list remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results. This study provides a comprehensive and effective method for performance evaluation of SSG and also innovates the weights calculation for traditional TOPSIS.

  13. Evaluation of Sustainable Development Indicators With Fuzzy TOPSIS Based on Subjective and Objective Weights

    Directory of Open Access Journals (Sweden)

    Nang Idayu Nik Zahari

    2012-04-01

    Full Text Available ABSTRACT: Sustainable development aims at improving and maintaining the well-being of people and the ecology. However, this paper focuses only on the ecological aspects. The selection of the proper ecological protection determinant plays a very important role in improving the environment of Malaysia. This paper will propose a method from Wang and Lee (2009, and Yong (2006 which applies a fuzzy TOPSIS method -- based on subjective and objective weights – to make the required selection. Four alternatives will be tested which are: prevent pollution (A1, conservation (A2, well-manage (A3, and public awareness (A4. Along with these, four criteria need to be considered: water quality factor (C1, land integrity factor (C2, air quality factor (C3, and biodiversity factor (C4. Finally, a numerical example of ecological protection determinant selection is used to illustrate the proposed method. ABSTRAK: Pembangunan lestari bermatlamat memperbaiki dan mengekalkan kesejahteraan rakyat serta ekologi. Walau bagaimanapun, kertas kajian ini hanya memberi tumpuan kepada aspek-aspek ekologi. Pemilihan penentu perlindungan serta keselamatan bagi aspek ekologi memainkan peranan yang amat penting dalam meningkatkan kualiti alam sekitar di Malaysia. Kertas kajian ini telah menggunakan kaedah Wang dan Lee (2009 dan Yong (2006 yang mengaplikasikan kaedah TOPSIS kabur berdasarkan pemberat subjektif dan objektif. Terdapat empat alternatif yang akan diuji iaitu: pencegahan pencemaran (A1, pemuliharaan (A2, pengurusan yang baik (A3, kesedaran orang awam (A4. Selain itu, terdapat empat kriteria yang perlu dipertimbangkan: faktor kualiti air (C1, faktor kualiti tanah (C2, faktor kualiti udara (C3, faktor kepelbagaian biologi (C4. Kesimpulannya, contoh pengiraan untuk memperoleh penentu pemilihan perlindungan ekologi telah digunakan bagi menunjukkan kaedah yang dicadangkan.KEYWORDS: sustainable development; ecological factors; subjective and objective weight; fuzzy TOPSIS

  14. Development of fuzzy multi-criteria approach to prioritize locations of treated wastewater use considering climate change scenarios.

    Science.gov (United States)

    Chung, Eun-Sung; Kim, Yeonjoo

    2014-12-15

    This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. An Interval-Valued Intuitionistic Fuzzy TOPSIS Method Based on an Improved Score Function

    Directory of Open Access Journals (Sweden)

    Zhi-yong Bai

    2013-01-01

    Full Text Available This paper proposes an improved score function for the effective ranking order of interval-valued intuitionistic fuzzy sets (IVIFSs and an interval-valued intuitionistic fuzzy TOPSIS method based on the score function to solve multicriteria decision-making problems in which all the preference information provided by decision-makers is expressed as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by IVIFS value and the information about criterion weights is known. We apply the proposed score function to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s can be selected in the decision-making process. Finally, two illustrative examples for multicriteria fuzzy decision-making problems of alternatives are used as a demonstration of the applications and the effectiveness of the proposed decision-making method.

  16. A Comparative Assesment of Facility Location Problem via fuzzy TOPSIS and fuzzy VIKOR: A Case Study on Security Services

    Directory of Open Access Journals (Sweden)

    Dilşad GÜZEL

    2015-05-01

    Full Text Available Today, law enforcement and security services are critically important for peace and prosperity of communities. The law enforcement forces serve citizens using security materials. The distribution of security materials is the dominant factor in determining the outcome of law enforcement duties. Failing to supply the required amounts of security materials properly, when and where it is needed, can lead to chaos. In this study, it is aimed to provide a decision support tool that can help to select the most appropriate location of security materials distribution center. The distribution center location problem is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. We proposed a comparative analysis that exploits fuzzy TOPSIS and fuzzy VIKOR techniques. Fuzzy weights of the 20 criteria and fuzzy judgments about 4 potential locations of distribution center as alternatives are employed to compute evaluation scores and ranking. Based on the evaluation criteria, Konya has been found the best alternative accourding to both techniques as well.

  17. Portfolio optimization using a hybrid of fuzzy ANP, VIKOR and TOPSIS

    Directory of Open Access Journals (Sweden)

    Reza Raei

    2012-10-01

    Full Text Available One of the primary questions in asset management is to find good combinations of different assets and this has been an interesting area of research for over half a century. The proposed model of this paper uses decision makers' feedbacks based on multiple criteria decision making technique to find an appropriate portfolio. We first select some important financial criteria and then using decision makers' opinions and by implementation of some fuzzy network analysis we find appropriate weights of the asset. The proposed model uses two multiple criteria techniques namely TOPSIS and VIKOR and the model is examined for some real-world data from Tehran Stock Exchange. The results of the implementation of the proposed model have been examined against Markowitz traditional model. The preliminary results indicate that the proposed model of this paper performs reasonably well compared with alternative method.

  18. Ranking Tehran’s Stock Exchange Top Fifty Stocks Using Fundamental Indexes and Fuzzy TOPSIS

    Directory of Open Access Journals (Sweden)

    E. S. Saleh

    2017-08-01

    Full Text Available Investment through the purchase of securities, constitute an important part of countries economic exchange. Therefore, making decisions about investing in a particular stock has become one of the most controversial areas of economic and financial research and various institutions have began to rank companies stock and determine priorities of stock purchase to investment. The current research, with the determination of important required indexes for companies ranking based on their shares value on the Tehran stock exchange, can greatly help to the accurate ranking of fifty premier listed companies. Initial ranking indicators are extracted and then a decision-making group (exchange experts with the use of the Delphi method and also non-parametric statistic methods, determines the final indexes. Then, by using Fuzzy ANP, weight criteria are obtained with taking into account their interaction with each other. Finally, using fuzzy TOPSIS and information extraction about the premier fifty listed companies of Tehran stock exchange in 2014 are ranked with the software "Rahavard Novin”. Sensitivity analysis to criteria weight and relevant analysis presentation was conducted at the end of the study procedures.

  19. Surface Water Quality Assessment and Prioritize the Factors Pollute This Water Using Topsis Fuzzy Hierarchical Analysis

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    Mehdi Komasi

    2017-03-01

    Full Text Available Background & Objective: Nowadays, according to growth of industry and increasing population, water resources are seriousely shortened. This lack of water resources will require special management to be considered in industry and agriculture. Among the various sources of water, surface waters are more susceptible to infection. The most important of these sources of pollution are industrial pollution, detergent, pesticides, radioactive materials, heat and salt concentration.  Materials & methods: In this article, at first the importance of each pollutant will be evaluated base on the effects and its results and then quality evaluation of surface water will be studied. In order to assess the relative importance of these pollutants primarily using TOPSIS software, prioritize these factors as one of the hierarchical analysis and then is modeled with decision tree method using Weka software, the importance of each factor is evaluated and if it does not meet the minimal importance of the decision tree will be removed. Results: The results obtained from the Topsis fuzzy analysis indicate that surface water and groundwater are exposed to pollution about 74% and 26% respectively among the six pollutants examined in this study. In addition, results obtaned from the hierarchical tree in software Weka has shown that the heat factor, soluble salts and industrial pollutants give impac factor or purity about 0.1338, 0.0523 and 1.2694 respectively. Conclusion: Surface water is at greater risk of being polluted compared with groundwater. The heat factor and low concentration of dissolved salts have the low impact and industrial pollutants are considered as the most influential factors in surface water pollution.

  20. Comparing performance of organization on implementation of customer relationship management systems using ANP and TOPSIS hybrid approach

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    A. Abedi

    2017-01-01

    Full Text Available As the customers are the main reason of the formation and survival of the organization, not only understanding their obvious needs, but also forecasting, determining and guiding their hidden needs, design and implementing plans of offering services for meeting these needs for attracting customers are among cornerstone of any activity in the organization. In this research, one compares the performance of e-commerce organizations, including three firms, namely Dijikala, Bamilo and Iranian regarding the implementation of Customer Relationship Management system using multiple criteria decision making approach. Along with this, hybrid fuzzy multiple criteria decision-making approach, including fuzzy network analysis has been used for examining the priority of each one of the dimensions and indexes of the proposed model and fuzzy TOPSIS technic for examining discussed options priority. The statistical population of this paper includes 12 experts, including directors and managements and assistances of three e-commerce firms. The results obtained from the study show that customer output group has the highest weight among other variables. Similarly, among evaluated indexes, the customer loyalty dimension has the highest weight in the implementation of Customer Relationship Management. The results of TOPSIS approach also show that among the studied firms, Dijikala has the best performance in implementing Customer Relationship Management.

  1. Application of Fuzzy Delphi TOPSIS to Locate Logistics Centers in Vietnam: The Logisticians’ Perspective

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    Thi Yen Pham

    2017-12-01

    Full Text Available Logistics centers have emerged as an important logistics infrastructure in supply chains. Hence, the problem of locating logistics centers plays a crucial role in designing and practicing logistics and supply chain management. Acknowledging the significance of logistics centers, Vietnam approved a master plan for the development of a logistics center system. However, the plan has been difficult to implementation because of the lack of the prioritization of the determinants used to locate logistics centers. This study aims to develop a benchmarking framework for choosing the locations of logistics centers based on the findings of logisticians by applying a hybrid of the fuzzy method and the technique for order of preference by similarity to ideal solution (TOPSIS, both of which are utilized extensively to overcome problems in selecting locations. The results indicate that freight demand, closeness to market, production area, customers, and transportation costs are regarded as the most important factors in deciding the location of logistics centers. In addition, among the three locations considered, the northeast provinces of Ho Chi Minh City were the best location for logistic centers, followed by North Hanoi and Da Nang city. The findings of this study make a significant contribution to both academic and practical aspects of locating logistic centers.

  2. A framework to overcome barriers to green innovation in SMEs using BWM and Fuzzy TOPSIS.

    Science.gov (United States)

    Gupta, Himanshu; Barua, Mukesh Kumar

    2018-08-15

    Recent years have witnessed a significant rise in exploring the barriers which obstruct adoption of green practices by SMEs. There is a constant need to innovate in terms of products, processes, and management so that we can overcome these barriers to green practices adoption and implementation. This study employs a three-phase methodology to identify barriers and solutions to overcome these barriers to green innovation in SMEs. Through extensive literature review and the opinion of selective manager's, seven main category barriers, thirty-six sub-category barriers, and twenty solutions to overcome these barriers were identified. BWM is used to rank these barriers and Fuzzy TOPSIS is used to rank solutions to overcome these barriers. Four Indian SMEs are taken to exemplify the proposed three paged model. To check the robustness of the model, a sensitivity analysis was also performed. The results of the analysis can act as a stepping stone for SME managers to eliminate and overcome barriers to green innovation in their firm and compete healthily in the market. The paper sets a framework for future studies in this area of research-work. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. EVALUATION AND RANKING OF ARTIFICIAL HIP PROSTHESIS SUPPLIERS BY USING A FUZZY TOPSIS METHODOLOGY

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    Marija Zahar Djordjevic

    2014-06-01

    Full Text Available The aim of this study is to propose a fuzzy multi-criteria decision-making approach (MCDM to evaluate the artificial hip prosthesis suppliers with respect to numerous criteria, simultaneously, taking into account the type of each criteria and its relative importance. The fuzzy of the Technique for Order Preference by Similarity to Ideal Solution (FTOSISis applied in order to rank the artificial hip prosthesis suppliers. The rank is obtained using the process of fuzzy number comparison. Software solution based on suggested method is also presented. A real-life example with real data is presented to clarify the proposed method.

  4. Uma comparação entre os métodos TOPSIS e Fuzzy-TOPSIS no apoio à tomada de decisão multicritério para seleção de fornecedores

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    Francisco Rodrigues Lima Junior

    2015-03-01

    Full Text Available A seleção de fornecedores é considerada a atividade mais crítica da função de compras e impacta diretamente a qualidade dos produtos manufaturados e o desempenho do comprador. Na literatura acadêmica, dezenas de métodos de tomada de decisão multicritério vêm sendo explorados para apoiar a seleção de fornecedores. Dentre esses, o TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution e o Fuzzy-TOPSIS (uma adaptação do primeiro se destacam por sua simplicidade de uso e pela capacidade de avaliar um número ilimitado de alternativas e critérios simultaneamente. Embora muitos autores sugiram a adoção do TOPSIS e do Fuzzy-TOPSIS para suportar a seleção de fornecedores, na literatura não são discutidas as reais vantagens de uso e as limitações destes métodos quando aplicados neste domínio de problema. Diante de tal lacuna, este estudo compara o TOPSIS e o Fuzzy-TOPSIS, em relação à complexidade computacional, à estrutura dos algoritmos e aos resultados fornecidos quando aplicados em um mesmo caso real de seleção de fornecedores. Os métodos foram implementados usando MATLAB(r e aplicados na seleção de fornecedores de uma empresa de cabos de transmissão. Os resultados mostram que o TOPSIS requer menor esforço para coleta de dados e processamento computacional. Em contrapartida, o Fuzzy-TOPSIS não sofre inversões no ranking e se mostra adequado para lidar com informações qualitativas e imprecisas. Os resultados deste estudo podem orientar pesquisadores e profissionais na escolha do método mais adequado para lidar com o problema de seleção de fornecedores em questão.

  5. Uma comparação entre os métodos TOPSIS e Fuzzy-TOPSIS no apoio à tomada de decisão multicritério para seleção de fornecedores

    OpenAIRE

    Lima Junior,Francisco Rodrigues; Carpinetti,Luiz Cesar Ribeiro

    2015-01-01

    A seleção de fornecedores é considerada a atividade mais crítica da função de compras e impacta diretamente a qualidade dos produtos manufaturados e o desempenho do comprador. Na literatura acadêmica, dezenas de métodos de tomada de decisão multicritério vêm sendo explorados para apoiar a seleção de fornecedores. Dentre esses, o TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e o Fuzzy-TOPSIS (uma adaptação do primeiro) se destacam por sua simplicidade de uso e pela...

  6. Comparing fuzzy AHP and fuzzy TOPSIS for evaluation of business intelligence vendors

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    Alireza Soloukdar

    2015-04-01

    Full Text Available The main objective of this study is to identify the most important criteria and indicators in selection of business intelligence vendors, and ranking the vendors of such tools using Fuzzy Analytical hierarchy Process (FAHP and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS, to compare results of these two methods and to provide appropriate solutions for the sample company, namely National Iranian Oil Company (NIOC. Spearman's rank correlation test was used for comparing the methods and determining their correlation. A strong positive correlation was observed between the ranks of business intelligence tools at the significance level of 0.05 in both methods. The results of the ranking by means of FAHP method show that IBM Company was the best one, followed by Oracle, SAS, QlikTech, SAP and Microsoft. However, based on the FTOPSIS method, Oracle was the leading company, followed by IBM, SAS and SAP and finally Microsoft.

  7. The evaluation of supply chain performance in the Oil Products Distribution Company, using information technology indicators and fuzzy TOPSIS technique

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    Daryosh Mohamadi Janaki

    2018-08-01

    Full Text Available Information Technology (IT plays an essential role on development of effective supply chain planning and it can improve the supply chain performance, either directly or indirectly. As a national industry, the National Iranian Oil Products Distribution Company involves a large number of organizations within its supply chain. Therefore, this descriptive-survey uses information sharing indicators, fuzzy TOPSIS technique based on managers and expert opinions to evaluate and to rank some oil products distribution companies. Data are analyzed and the results show that Oil Products Distribution Company of Chaharmahal and Bakhtiari received the highest rank and Farsan maintained the lowest rank compared with other regional companies.

  8. A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry

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    Muhammad Nazam

    2015-05-01

    Full Text Available In the emerging supply chain environment, green supply chain risk management plays a significant role than ever. Risk is an inherent uncertainty and has tendency to disrupt the typical green supply chain management (GSCM operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM which could evaluate the potential risks in the context of (GSCM is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS methodology to rank and assess the risks associated with implementation of (GSCM practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.

  9. Application of Grey-TOPSIS approach to evaluate value chain performance of tea processing chains

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    Richard Nyaoga

    2016-03-01

    Full Text Available This study develops an effective method to measure value chain performance and rank them based on qualitative criteria and to determine the ranking order of the various forms of performance under study. This approach integrates the advantage of grey systems theory and TOPSIS to evaluate and rank value chain performance. Grey-TOPSIS approach has been applied to measure and rank the value chain performance of various firms. The results indicate that the proposed model is useful to facilitate multi-criteria decision-making (MCDM problem under the environment of uncertainty and vagueness. The model also provides an appropriate ranking order based on the available alternatives. The Grey-TOPSIS approach that will be useful to the managers to use for solving the similar type of decision-making problems in their firms in the future has been discussed. Even though, the problem of choosing a suitable performance option is often addressed in practice and research, very few studies are available in the literature of Grey-TOPSIS decision models. Also, Grey-TOPSIS model application in the tea processing firms is non-existence hence this study is the very first to apply this model in evaluating value chain performance in the tea processing firms.

  10. Seeking the Important Nodes of Complex Networks in Product R&D Team Based on Fuzzy AHP and TOPSIS

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    Wei Zhang

    2013-01-01

    Full Text Available How to seek the important nodes of complex networks in product research and development (R&D team is particularly important for companies engaged in creativity and innovation. The previous literature mainly uses several single indicators to assess the node importance; this paper proposes a multiple attribute decision making model to tentatively solve these problems. Firstly, choose eight indicators as the evaluation criteria, four from centralization of complex networks: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality and four from structural holes of complex networks: effective size, efficiency, constraint, and hierarchy. Then, use fuzzy analytic hierarchy process (AHP to obtain the weights of these indicators and use technique for order preference by similarity to an ideal solution (TOPSIS to assess the importance degree of each node of complex networks. Finally, taking a product R&D team of a game software company as a research example, test the effectiveness, operability, and efficiency of the method we established.

  11. DETERMINING THE PREFERENCE OF GSM OPERATORS IN TURKEY WITH FUZZY TOPSIS AFTER MOBILE NUMBER PORTABILITY SYSTEM APPLICATION

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    Nihal ERGİNEL

    2010-12-01

    Full Text Available Mobile number portability systems is a system that can allow portability of GSM (Global System for Mobile Communications number from another operator without changing GSM number. There are several criteria to select the GSM operators by customer after this system is legal in Turkey. The main purpose of this study is to determine the market sharing in the future of GSM operators by expressing the weighting grades of selection criteria and the relationship between criteria and alternatives that include uncertainty as fuzzy triangular numbers. In this study, the selection criteria of GSM operators are defined form literature and views of customer and weighted with linguistic variables by working group. Avea, Turkcell and Vodafone that active in Turkey are graded with linguistic variables to each criterion. Analyzing linguistic variables as qualitative variables and using graded linguistic variables in a specified interval are required fuzzy multi-criteria decision making methods. Expected market sharing of GSM operators is determined by using fuzzy TOPSIS method.

  12. Comparative Analysis of AHP-TOPSIS and Fuzzy AHP Models in Selecting Appropriate Nanocomposites for Environmental Noise Barrier Applications

    Science.gov (United States)

    Naderzadeh, Mahdiyeh; Arabalibeik, Hossein; Monazzam, Mohammad Reza; Ghasemi, Ismaeil

    Choosing the right material in the design of environmental noise barriers has always been a challenging issue in acoustics. In less-developed countries, the material selection is affected by many factors from various aspects, which makes the decision-making very complicated. This study attempts to compare and assign weights to the most important indices affecting the choice of appropriate noise barrier material. These criteria include absorption coefficient, transparency, tensile modulus, strength at yield, elongation at break, impact strength, flexural modulus, hardness, and cost. For this purpose, experts' opinions was gathered through a total of 13 questionnaires and used for assigning weights by Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy process (FAHP) techniques. According to the AHP results, impact strength, with only a minor difference of 0.093 compared to the AHP, was recognized as the most important criterion. Finally, the optimal composite material was selected using two different methods; first by Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS) based on the weights obtained from AHP, and next by directly applying the obtained weights from FAHP to the true measured values of parameters. As the results show, in both abovementioned methods, Polycarbonate-SiO2 0.3% with roughened surface (PCSI3-R) received the highest score and was selected as the preferred composite material. Given the close similarity of the results, to determine the superiority of one method over the other, some noise was added to the original data set from the mechanical and acoustic tests and then the variance of the changes in the final orders of preferences was calculated. This indicates the robustness of the method against the measurement errors and noise. The results shows that under the same circumstances, the overall order shift variance in the classic TOPSIS is six times higher than that of the fuzzy AHP method.

  13. TOPSIS with statistical distances: A new approach to MADM

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    Vijaya Babu Vommi

    2017-01-01

    Full Text Available Multiple attribute decision making (MADM methods are very useful in choosing the best alternative among the available finite but conflicting alternatives. TOPSIS is one of the MADM methods, which is simple in its methodology and logic. In TOPSIS, Euclidean distances of each alternative from the positive and negative ideal solutions are utilized to find the best alternative. In literature, apart from Euclidean distances, the city block distances have also been tried to find the separations measures. In general, the attribute data are distributed with unequal ranges and also possess moderate to high correlations. Hence, in the present paper, use of statistical distances is proposed in place of Euclidean distances. Procedures to find the best alternatives are developed using statistical and weighted statistical distances respectively. The proposed methods are illustrated with some industrial problems taken from literature. Results show that the proposed methods can be used as new alternatives in MADM for choosing the best solutions.

  14. A Large Group Decision Making Approach Based on TOPSIS Framework with Unknown Weights Information

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    Li Yupeng

    2017-01-01

    Full Text Available Large group decision making considering multiple attributes is imperative in many decision areas. The weights of the decision makers (DMs is difficult to obtain for the large number of DMs. To cope with this issue, an integrated multiple-attributes large group decision making framework is proposed in this article. The fuzziness and hesitation of the linguistic decision variables are described by interval-valued intuitionistic fuzzy sets. The weights of the DMs are optimized by constructing a non-linear programming model, in which the original decision matrices are aggregated by using the interval-valued intuitionistic fuzzy weighted average operator. By solving the non-linear programming model with MATLAB®, the weights of the DMs and the fuzzy comprehensive decision matrix are determined. Then the weights of the criteria are calculated based on the information entropy theory. At last, the TOPSIS framework is employed to establish the decision process. The divergence between interval-valued intuitionistic fuzzy numbers is calculated by interval-valued intuitionistic fuzzy cross entropy. A real-world case study is constructed to elaborate the feasibility and effectiveness of the proposed methodology.

  15. Evaluation of E-Learning Web Sites Using Fuzzy Axiomatic Design Based Approach

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    2010-04-01

    Full Text Available High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered.

  16. SELECTION OF PROJECT MANAGERS IN CONSTRUCTION FIRMS USING ANALYTIC HIERARCHY PROCESS (AHP AND FUZZY TOPSIS: A CASE STUDY

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    Fatemeh Torfi

    2011-10-01

    Full Text Available Selecting a project manager is a major decision for every construction company. Traditionally, a project manager is selected by interviewing applicants and evaluating their capabilities by considering the special requirements of the project. The interviews are usually conducted by senior managers, and the selection of the best candidate depends on their opinions. Thus, the results may not be completely reliable. Moreover, conducting interviews for a large group of candidates is time-consuming. Thus, there is a need for computational models that can be used to select the most suitable applicant, given the project specifications and the applicants’ details. In this paper, a case study is performed in which a Fuzzy Multiple Criteria Decision Making (FMCDM model is used to select the best candidate for the post of project manager in a large construction firm. First, with the opinions of the senior managers, all the criteria and sub-criteria required for the selection are gathered, and the criteria priorities are qualitatively specified. Then, the applicants are ranked using the Analytic Hierarchy Process (AHP, approximate weights of the criteria, and fuzzy technique for order performance by similarity to ideal solution (TOPSIS. The results of the case study are shown to be satisfactory.

  17. Flood control project selection using an interval type-2 entropy weight with interval type-2 fuzzy TOPSIS

    Science.gov (United States)

    Zamri, Nurnadiah; Abdullah, Lazim

    2014-06-01

    Flood control project is a complex issue which takes economic, social, environment and technical attributes into account. Selection of the best flood control project requires the consideration of conflicting quantitative and qualitative evaluation criteria. When decision-makers' judgment are under uncertainty, it is relatively difficult for them to provide exact numerical values. The interval type-2 fuzzy set (IT2FS) is a strong tool which can deal with the uncertainty case of subjective, incomplete, and vague information. Besides, it helps to solve for some situations where the information about criteria weights for alternatives is completely unknown. Therefore, this paper is adopted the information interval type-2 entropy concept into the weighting process of interval type-2 fuzzy TOPSIS. This entropy weight is believed can effectively balance the influence of uncertainty factors in evaluating attribute. Then, a modified ranking value is proposed in line with the interval type-2 entropy weight. Quantitative and qualitative factors that normally linked with flood control project are considered for ranking. Data in form of interval type-2 linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. Study is considered for the whole of Malaysia. From the analysis, it shows that diversion scheme yielded the highest closeness coefficient at 0.4807. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the diversion scheme recorded the first rank among five causes.

  18. A Novel MADM Approach Based on Fuzzy Cross Entropy with Interval-Valued Intuitionistic Fuzzy Sets

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    Xin Tong

    2015-01-01

    Full Text Available The paper presents a novel multiple attribute decision-making (MADM approach for the problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy sets (IVIFS. First, the fuzzy cross entropy and discrimination degree of IVIFS are defied. Subsequently, based on the discrimination degree of IVIFS, a nonlinear programming model to minimize the total deviation of discrimination degrees between alternatives and the positive ideal solution PIS as well as the negative ideal solution (NIS is constructed to obtain the attribute weights and, then, the weighted discrimination degree. Finally, all the alternatives are ranked according to the relative closeness coefficients using the extended TOPSIS method, and the most desirable alternative is chosen. The proposed approach extends the research method of MADM based on the IVIF cross entropy. Finally, we illustrate the feasibility and validity of the proposed method by two examples.

  19. Proposing a framework for airline service quality evaluation using Type-2 Fuzzy TOPSIS and non-parametric analysis

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    Navid Haghighat

    2017-12-01

    Full Text Available This paper focuses on evaluating airline service quality from the perspective of passengers' view. Until now a lot of researches has been performed in airline service quality evaluation in the world but a little research has been conducted in Iran, yet. In this study, a framework for measuring airline service quality in Iran is proposed. After reviewing airline service quality criteria, SSQAI model was selected because of its comprehensiveness in covering airline service quality dimensions. SSQAI questionnaire items were redesigned to adopt with Iranian airlines requirements and environmental circumstances in the Iran's economic and cultural context. This study includes fuzzy decision-making theory, considering the possible fuzzy subjective judgment of the evaluators during airline service quality evaluation. Fuzzy TOPSIS have been applied for ranking airlines service quality performances. Three major Iranian airlines which have the most passenger transfer volumes in domestic and foreign flights were chosen for evaluation in this research. Results demonstrated Mahan airline has got the best service quality performance rank in gaining passengers' satisfaction with delivery of high-quality services to its passengers, among the three major Iranian airlines. IranAir and Aseman airlines placed in the second and third rank, respectively, according to passenger's evaluation. Statistical analysis has been used in analyzing passenger responses. Due to the abnormality of data, Non-parametric tests were applied. To demonstrate airline ranks in every criterion separately, Friedman test was performed. Variance analysis and Tukey test were applied to study the influence of increasing in age and educational level of passengers on degree of their satisfaction from airline's service quality. Results showed that age has no significant relation to passenger satisfaction of airlines, however, increasing in educational level demonstrated a negative impact on

  20. A DEA-TOPSIS approach for ranking credit institutions

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    Mohammad Ehsani

    2014-09-01

    Full Text Available Measuring the relative efficiency of financial units plays essential role for making strategic decisions such as business development, downsizing, etc. This paper presents an empirical investigation to rank different branches of a credit institution named Samen in city of Semnan, Iran. The proposed study uses data envelopment analysis (DEA for measuring the relative efficiency of 17 units. The results indicate that five units were efficient and using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS, the efficient units are ranked based on some inputs/outputs. The results of this study indicate that most branches of this financial unit performed poorly and a restructure in their businesses is necessary. In addition, the study has provided some evidences that considering employee wage, bank deposit and administration expenses as inputs for DEA implementation seems to provide better results than using total assets and equities.

  1. Using SWAT and Fuzzy TOPSIS to Assess the Impact of Climate Change in the Headwaters of the Segura River Basin (SE Spain

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    Javier Senent-Aparicio

    2017-02-01

    Full Text Available The Segura River Basin is one of the most water-stressed basins in Mediterranean Europe. If we add to the actual situation that most climate change projections forecast important decreases in water resource availability in the Mediterranean region, the situation will become totally unsustainable. This study assessed the impact of climate change in the headwaters of the Segura River Basin using the Soil and Water Assessment Tool (SWAT with bias-corrected precipitation and temperature data from two Regional Climate Models (RCMs for the medium term (2041–2070 and the long term (2071–2100 under two emission scenarios (RCP4.5 and RCP8.5. Bias correction was performed using the distribution mapping approach. The fuzzy TOPSIS technique was applied to rank a set of nine GCM–RCM combinations, choosing the climate models with a higher relative closeness. The study results show that the SWAT performed satisfactorily for both calibration (NSE = 0.80 and validation (NSE = 0.77 periods. Comparing the long-term and baseline (1971–2000 periods, precipitation showed a negative trend between 6% and 32%, whereas projected annual mean temperatures demonstrated an estimated increase of 1.5–3.3 °C. Water resources were estimated to experience a decrease of 2%–54%. These findings provide local water management authorities with very useful information in the face of climate change.

  2. TOPSIS-based consensus model for group decision-making with incomplete interval fuzzy preference relations.

    Science.gov (United States)

    Liu, Fang; Zhang, Wei-Guo

    2014-08-01

    Due to the vagueness of real-world environments and the subjective nature of human judgments, it is natural for experts to estimate their judgements by using incomplete interval fuzzy preference relations. In this paper, based on the technique for order preference by similarity to ideal solution method, we present a consensus model for group decision-making (GDM) with incomplete interval fuzzy preference relations. To do this, we first define a new consistency measure for incomplete interval fuzzy preference relations. Second, a goal programming model is proposed to estimate the missing interval preference values and it is guided by the consistency property. Third, an ideal interval fuzzy preference relation is constructed by using the induced ordered weighted averaging operator, where the associated weights of characterizing the operator are based on the defined consistency measure. Fourth, a similarity degree between complete interval fuzzy preference relations and the ideal one is defined. The similarity degree is related to the associated weights, and used to aggregate the experts' preference relations in such a way that more importance is given to ones with the higher similarity degree. Finally, a new algorithm is given to solve the GDM problem with incomplete interval fuzzy preference relations, which is further applied to partnership selection in formation of virtual enterprises.

  3. Presenting a mapping method based on fuzzy Logic and TOPSIS multi criteria decision-making methods to detect promising porphyry copper mineralization areas in the east of the Sarcheshmeh copper metallogenic district

    Directory of Open Access Journals (Sweden)

    Shokouh Riahi

    2017-11-01

    Full Text Available Introduction The growing demand for base metals such as iron, copper, lead and zinc on the one hand and the diminishing of surficial and shallow resources of these elements on the other hand have forced explorationists to focus on detecting deep deposits of these metals. As a result, the discovery of such deep deposits requires more advanced and sophisticated methods in the course of preliminary prospecting stages. Since the discovery of new deposits is getting to be increasingly difficult, deploying new prospecting technologies that employ more deposit attributes in the course of combining exploratory evidence may reduce the exploration costs with lower uncertainties. In the past two decades, a number of new data mining and integrating approaches capable of incorporating direct and indirect mineralization indicators, based on expert knowledge, data, or a combination of both, have been proposed Bonham-Carter, 1994(. In the first step, the input exploratory data layers are corrected and validated through applying some statistical pre-processing algorithms such as background and outlier removal methods. In order to detect a mineralization occurrence, it is necessary to find the proper exploratory geological, geochemical and geophysical data layers which have direct or indirect associations with the governing mineralization followed by constructing these models in an appropriate GIS platform (Malkzewski, 1999. Due to the imperfect available data and a number of unknown parameters affecting the mineralization process, the application of conventional GIS integration methods such as Boolean or weighted overlay or even fuzzy logic methods alone may not produce appropriate results, pointing to a need for deploying multi-criteria decision-making methods such as TOPSIS. In the present study, the pre-processed exploratory data including geological, remotely sensed geophysical and geochemical imagery were used to detect favorable mineralization zones

  4. Comparação entre os métodos Fuzzy TOPSIS e Fuzzy AHP no apoio à tomada de decisão para seleção de fornecedores

    OpenAIRE

    Francisco Rodrigues Lima Junior

    2013-01-01

    A seleção de fornecedores tem impacto significante no custo e na qualidade de produtos manufaturados. Por isso, a seleção de fornecedores passou a ser vista como uma atividade bastante crítica para o desempenho da empresa compradora. Muitos estudos da literatura propõem o uso dos métodos multicritério fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e fuzzy AHP (Analytic Hierarchy Process) para apoiar a seleção de fornecedores. Contudo, não são encontrados estu...

  5. Strategic planning decision making using fuzzy SWOT-TOPSIS with reliability factor

    Science.gov (United States)

    Mohamad, Daud; Afandi, Nur Syamimi; Kamis, Nor Hanimah

    2015-10-01

    Strategic planning is a process of decision making and action for long-term activities in an organization. The Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis has been commonly used to help organizations in strategizing their future direction by analyzing internal and external environment. However, SWOT analysis has some limitations as it is unable to prioritize appropriately the multiple alternative strategic decisions. Some efforts have been made to solve this problem by incorporating Multi Criteria Decision Making (MCDM) methods. Nevertheless, another important aspect has raised concerns on obtaining the decision that is the reliability of the information. Decision makers evaluate differently depending on their level of confidence or sureness in the evaluation. This study proposes a decision making procedure for strategic planning using SWOT-TOPSIS method by incorporating the reliability factor of the evaluation based on Z-number. An example using a local authority in the east coast of Malaysia is illustrated to determine the strategic options ranking and to prioritize factors in each SWOT category.

  6. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    Science.gov (United States)

    Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

    2017-11-01

    This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

  7. Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

    Science.gov (United States)

    Chaharsooghi, S K; Ashrafi, Mehdi

    2014-01-01

    Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

  8. An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

    Directory of Open Access Journals (Sweden)

    Burak Erkayman

    2012-01-01

    Full Text Available Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

  9. An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

    Science.gov (United States)

    Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

    2012-01-01

    Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

  10. An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

    Science.gov (United States)

    Gundogar, Emin; Yılmaz, Aysegul

    2012-01-01

    Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

  11. Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

    Science.gov (United States)

    Lee, G.; Jun, K. S.; Chung, E.-S.

    2015-04-01

    This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

  12. The Attractiveness of CEE Countries For FDI. A Public Policy Approach Using the Topsis Method

    Directory of Open Access Journals (Sweden)

    Andreea PAUL

    2014-06-01

    Full Text Available This paper analyzes the location decision for foreign direct investments (FDI in Central and Eastern European (CEE countries based on the attractiveness of policies most influenced by public officials. Our assessment of the FDI inflows in a country is based on four pillars: infrastructure, quality of institutions, labor market and taxes. The attraction degree of the CEE countries in 2007 and 2010 is calculated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS method, a tool usually used for decision-making issues. The empirical result indicates that Estonia is the most attractive country for investments (as regards the public policy approach. Globally, the paper establishes the state’s role in attracting FDI and identifies whether there is room for further improvement on the public policy side.

  13. Fuzzy Continuous Review Inventory Model using ABC Multi-Criteria Classification Approach: A Single Case Study

    Directory of Open Access Journals (Sweden)

    Meriastuti - Ginting

    2015-07-01

    Full Text Available Abstract. Inventory is considered as the most expensive, yet important,to any companies. It representsapproximately 50% of the total investment. Inventory cost has become one of the majorcontributorsto inefficiency, therefore it should be managed effectively. This study aims to propose an alternative inventory model,  by using ABC multi-criteria classification approach to minimize total cost. By combining FANP (Fuzzy Analytical Network Process and TOPSIS (Technique of Order Preferences by Similarity to the Ideal Solution, the ABC multi-criteria classification approach identified 12 items of 69 inventory items as “outstanding important class” that contributed to 80% total inventory cost. This finding  is then used as the basis to determine the proposed continuous review inventory model.This study found that by using fuzzy trapezoidal cost, the inventory  turnover ratio can be increased, and inventory cost can be decreased by 78% for each item in “class A” inventory.Keywords:ABC multi-criteria classification, FANP-TOPSIS, continuous review inventory model lead-time demand distribution, trapezoidal fuzzy number 

  14. Fuzzy multiple linear regression: A computational approach

    Science.gov (United States)

    Juang, C. H.; Huang, X. H.; Fleming, J. W.

    1992-01-01

    This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.

  15. Optimization on Turning Parameters of 15-5PH Stainless Steel Using Taguchi Based Grey Approach and Topsis

    Directory of Open Access Journals (Sweden)

    Palanisamy D.

    2016-09-01

    Full Text Available The machinability and the process parameter optimization of turning operation for 15-5 Precipitation Hardening (PH stainless steel have been investigated based on the Taguchi based grey approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS. An L27 orthogonal array was selected for planning the experiment. Cutting speed, depth of cut and feed rate were considered as input process parameters. Cutting force (Fz and surface roughness (Ra were considered as the performance measures. These performance measures were optimized for the improvement of machinability quality of product. A comparison is made between the multi-criteria decision making tools. Grey Relational Analysis (GRA and TOPSIS are used to confirm and prove the similarity. To determine the influence of process parameters, Analysis of Variance (ANOVA is employed. The end results of experimental investigation proved that the machining performance can be enhanced effectively with the assistance of the proposed approaches.

  16. Fuzzy MCDM Approach for Evaluating Intangible Resources Affecting Port Service Quality

    Directory of Open Access Journals (Sweden)

    Ji Yeong Pak

    2015-12-01

    Full Text Available Intangible resources consist of soft resources such as knowledge, information and capabilities. It is important for ports to enhance intangible as well as tangible resources to obtain sustainable competitive advantage. In this connection, this study aims to identify port intangible resources which may contribute to the delivery of port service quality and to propose a fuzzy TOPSIS approach to solve the port choice problem focusing on intangible resources. Fuzzy TOPSIS is appropriate to assist decision making with ambiguous and uncertain problems such as port choice with respect to intangible resources. In this paper, five port intangible resources were identified and evaluated and five leading container ports in the Asia-Pacific region were assessed in terms of their intangible resources. A survey questionnaire was sent to 21 experts who are working in shipping companies in Korea and involved in the selection of ports. It was found that customer and relational resource contributes most to the delivery of port service quality while Hong Kong appeared to be the port where intangible resources were most highly evaluated. This research helps to enrich the literature on port service quality and port choice evaluation. Its findings can also be used as guidelines for port managers to prioritise resources that may have greater influence on the delivery of port service quality and the subsequent training and education programs.

  17. A Fuzzy Modeling Approach for Replicated Response Measures Based on Fuzzification of Replications with Descriptive Statistics and Golden Ratio

    Directory of Open Access Journals (Sweden)

    Özlem TÜRKŞEN

    2018-03-01

    Full Text Available Some of the experimental designs can be composed of replicated response measures in which the replications cannot be identified exactly and may have uncertainty different than randomness. Then, the classical regression analysis may not be proper to model the designed data because of the violation of probabilistic modeling assumptions. In this case, fuzzy regression analysis can be used as a modeling tool. In this study, the replicated response values are newly formed to fuzzy numbers by using descriptive statistics of replications and golden ratio. The main aim of the study is obtaining the most suitable fuzzy model for replicated response measures through fuzzification of the replicated values by taking into account the data structure of the replications in statistical framework. Here, the response and unknown model coefficients are considered as triangular type-1 fuzzy numbers (TT1FNs whereas the inputs are crisp. Predicted fuzzy models are obtained according to the proposed fuzzification rules by using Fuzzy Least Squares (FLS approach. The performances of the predicted fuzzy models are compared by using Root Mean Squared Error (RMSE criteria. A data set from the literature, called wheel cover component data set, is used to illustrate the performance of the proposed approach and the obtained results are discussed. The calculation results show that the combined formulation of the descriptive statistics and the golden ratio is the most preferable fuzzification rule according to the well-known decision making method, called TOPSIS, for the data set.

  18. Automatic approach to deriving fuzzy slope positions

    Science.gov (United States)

    Zhu, Liang-Jun; Zhu, A.-Xing; Qin, Cheng-Zhi; Liu, Jun-Zhi

    2018-03-01

    Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions.

  19. A combined approach of AHP and TOPSIS methods applied in the field of integrated software systems

    Science.gov (United States)

    Berdie, A. D.; Osaci, M.; Muscalagiu, I.; Barz, C.

    2017-05-01

    Adopting the most appropriate technology for developing applications on an integrated software system for enterprises, may result in great savings both in cost and hours of work. This paper proposes a research study for the determination of a hierarchy between three SAP (System Applications and Products in Data Processing) technologies. The technologies Web Dynpro -WD, Floorplan Manager - FPM and CRM WebClient UI - CRM WCUI are multi-criteria evaluated in terms of the obtained performances through the implementation of the same web business application. To establish the hierarchy a multi-criteria analysis model that combines the AHP (Analytic Hierarchy Process) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods was proposed. This model was built with the help of the SuperDecision software. This software is based on the AHP method and determines the weights for the selected sets of criteria. The TOPSIS method was used to obtain the final ranking and the technologies hierarchy.

  20. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    OpenAIRE

    Dhruba Das; Hemanta K. Baruah

    2015-01-01

    In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...

  1. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    concepts of fuzzy set theory and then define a fully fuzzy linear system of equations. .... To represent the above problem as fully fuzzy linear system, we represent x .... Fully fuzzy linear systems can be solved by Linear programming approach, ...

  2. A Fuzzy MCDM Approach for Green Supplier Selection from the Economic and Environmental Aspects

    Directory of Open Access Journals (Sweden)

    Hsiu Mei Wang Chen

    2016-01-01

    Full Text Available Due to the challenge of rising public awareness of environmental issues and governmental regulations, green supply chain management (SCM has become an important issue for companies to gain environmental sustainability. Supplier selection is one of the key operational tasks necessary to construct a green SCM. To select the most suitable suppliers, many economic and environmental criteria must be considered in the decision process. Although numerous studies have used economic criteria such as cost, quality, and lead time in the supplier selection process, only some studies have taken into account the environmental issues. This study proposes a comprehensive fuzzy multicriteria decision making (MCDM approach for green supplier selection and evaluation, using both economic and environmental criteria. In the proposed approach, a fuzzy analytic hierarchy process (AHP is employed to determine the important weights of criteria under vague environment. In addition, a fuzzy technique for order performance by similarity to ideal solution (TOPSIS is used to evaluate and rank the potential suppliers. Finally, a case study in Luminance Enhancement Film (LEF industry is presented to illustrate the applicability and efficiency of the proposed method.

  3. Radiotherapy problem under fuzzy theoretic approach

    International Nuclear Information System (INIS)

    Ammar, E.E.; Hussein, M.L.

    2003-01-01

    A fuzzy set theoretic approach is used for radiotherapy problem. The problem is faced with two goals: the first is to maximize the fraction of surviving normal cells and the second is to minimize the fraction of surviving tumor cells. The theory of fuzzy sets has been employed to formulate and solve the problem. A linguistic variable approach is used for treating the first goal. The solutions obtained by the modified approach are always efficient and best compromise. A sensitivity analysis of the solutions to the differential weights is given

  4. Multi-attribute Evaluation of Website Quality in E-business Using an Integrated Fuzzy AHPTOPSIS Methodology

    Directory of Open Access Journals (Sweden)

    Tolga Kaya

    2010-09-01

    Full Text Available Success of an e-business company is strongly associated with the relative quality of its website compared to that of its competitors. The purpose of this study is to propose a multi-attribute e-business website quality evaluation methodology based on a modified fuzzy TOPSIS approach. In the proposed methodology, weights of the evaluation criteria are generated by a fuzzy AHP procedure. In performance evaluation problems, the judgments of the experts may usually be vague in form. As fuzzy logic can successfully deal with this kind of uncertainty in human preferences, both classical TOPSIS and classical AHP procedures are implemented under fuzzy environment. The proposed TOPSIS-AHP methodology has successfully been applied to a multi-attribute website quality evaluation problem in Turkish e-business market. Nine sub-criteria under four main categories are used in the evaluation of the most popular e-business websites of Turkey. A sensitivity analysis is also provided.

  5. TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two-Stroke Petrol Engines

    Directory of Open Access Journals (Sweden)

    Masoud Dehghani Soufi

    2015-12-01

    Full Text Available Exhaust pollutants from two-stroke petrol engines are a problem for the environment. Biolubricants are a new generation of renewable and eco-friendly vegetable-based lubricants, which have attracted a lot of attention in recent years. In this paper, the applicability of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS method to support the process of building the scoring system for selecting an appropriate two-stroke lubricant has been analyzed. For this purpose, biolubricants (TMP-triesters based on castor oil, palm oil, and waste cooking oil were produced and then utilized in a 200 cc two-stroke gasoline engine to investigate their effects on its performance and exhaust emissions. The results obtained from the use of the entropy technique in the TOPSIS algorithm showed that palm oil-based lubricant took up the greatest distance from the Negative Ideal Solution (NIS and was selected as the most optimal lubricant for these types of engines.

  6. Improved TOPSIS decision model for NPP emergencies

    International Nuclear Information System (INIS)

    Zhang Jin; Liu Feng; Huang Lian

    2011-01-01

    In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants. Given the complexity of multi-attribute emergency decision-making on nuclear accident, the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index. A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect. (authors)

  7. Evaluation of Wheel Loaders in Open Pit Marble Quarrying by Using the AHP and Topsis Approaches / Ocena pracy ładowarki na podwoziu kołowym w odkrywkowej kopalni marmuru w oparciu o metody AHP i topsis

    Science.gov (United States)

    Kun, Mete; Topaloǧlu, Şeyda; Malli, Tahir

    2013-03-01

    The marble mining in Turkey has been rising since the early 80's. In relation to that, the marble income has become noticeably bigger than those of other mining sectors. In recent years, marble and natural stone export composes half of the total mine export with a value of two billion dollars. This rapid development observed in marble operation has increased the importance of mining economics, income-expenditure balance and cost analysis. The most important cost elements observed in marble quarrying are machinery and equipment, labor costs and geological structures of the field. The aim of this study is to is to propose a multi-criteria decision making (MCDM) approach to evaluate the wheel loader alternatives and select the best loader under multiple criteria. A two-step methodology based on two MCDM methods, which are namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation procedure. More precisely, AHP is applied to determine the relative weights of evaluation criteria and TOPSIS is applied to rank the wheel loader alternatives. The proposed approach also provides a relatively simple and very well suited decision making tool for this type of decision making problems.

  8. Fuzzy Multi-objective Linear Programming Approach

    Directory of Open Access Journals (Sweden)

    Amna Rehmat

    2007-07-01

    Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

  9. A Large Group Decision Making Approach Based on TOPSIS Framework with Unknown Weights Information

    OpenAIRE

    Li Yupeng; Lian Xiaozhen; Lu Cheng; Wang Zhaotong

    2017-01-01

    Large group decision making considering multiple attributes is imperative in many decision areas. The weights of the decision makers (DMs) is difficult to obtain for the large number of DMs. To cope with this issue, an integrated multiple-attributes large group decision making framework is proposed in this article. The fuzziness and hesitation of the linguistic decision variables are described by interval-valued intuitionistic fuzzy sets. The weights of the DMs are optimized by constructing a...

  10. Fuzzy set theoretic approach to fault tree analysis | Tyagi ...

    African Journals Online (AJOL)

    This approach can be widely used to improve the reliability and to reduce the operating cost of a system. The proposed techniques are discussed and illustrated by taking an example of a nuclear power plant. Keywords: Fault tree, Triangular and Trapezoidal fuzzy number, Fuzzy importance, Ranking of fuzzy numbers ...

  11. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    Directory of Open Access Journals (Sweden)

    Dhruba Das

    2015-04-01

    Full Text Available In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM/M/1 and M/FM/1 has been studied and constructed their membership functions of the system characteristics based on the aforesaid principle. The former represents a queue with fuzzy exponential arrivals and exponential service rate while the latter represents a queue with exponential arrival rate and fuzzy exponential service rate.

  12. Hesitant fuzzy methods for multiple criteria decision analysis

    CERN Document Server

    Zhang, Xiaolu

    2017-01-01

    The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...

  13. Supplier selection problem: A fuzzy multicriteria approach | Allouche ...

    African Journals Online (AJOL)

    The purpose of this paper is to suggest a fuzzy multi-criteria approach to solve the supplier selection problem, an approach based on the fuzzy analytic hierarchy process and imprecise goal programming. To deal with decision-maker (DM) preferences, the concept of satisfaction function is introduced. The proposed ...

  14. The fuzzy approach to statistical analysis

    NARCIS (Netherlands)

    Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.

    2006-01-01

    For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;

  15. Polynomial fuzzy observer designs: a sum-of-squares approach.

    Science.gov (United States)

    Tanaka, Kazuo; Ohtake, Hiroshi; Seo, Toshiaki; Tanaka, Motoyasu; Wang, Hua O

    2012-10-01

    This paper presents a sum-of-squares (SOS) approach to polynomial fuzzy observer designs for three classes of polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi-Sugeno (T-S) fuzzy controller and observer designs. First, we briefly summarize previous results with respect to a polynomial fuzzy system that is a more general representation of the well-known T-S fuzzy system. Next, we propose polynomial fuzzy observers to estimate states in three classes of polynomial fuzzy systems and derive SOS conditions to design polynomial fuzzy controllers and observers. A remarkable feature of the SOS design conditions for the first two classes (Classes I and II) is that they realize the so-called separation principle, i.e., the polynomial fuzzy controller and observer for each class can be separately designed without lack of guaranteeing the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. Although, for the last class (Class III), the separation principle does not hold, we propose an algorithm to design polynomial fuzzy controller and observer satisfying the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. All the design conditions in the proposed approach can be represented in terms of SOS and are symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. To illustrate the validity and applicability of the proposed approach, three design examples are provided. The examples demonstrate the advantages of the SOS-based approaches for the existing LMI approaches to T-S fuzzy observer designs.

  16. EVALUATION OF SERVICE QUALITY OF AIRWAY COMPANIES GIVING DOMESTIC SERVICES IN TURKEY WITH FUZZY SET APPROACH

    Directory of Open Access Journals (Sweden)

    H. Handan DEMIR

    2013-01-01

    Full Text Available Today, service quality has become a major phenomenon with the requirement of meeting consumer demands in the best way brought along with the rising competition between companies. Airway transportation is preferred more and more during the recent years. Many qualitative and quantitative criteria are considered while evaluating service criteria in airway transportation. In this context, evaluation of service quality is a decisionmaking problem with many criteria. The purpose of this study is to evaluate service quality of domestic airway companies in Turkey. In this study; fuzzy TOPSIS method which is one of the most preferred fuzzy MCDM methods, extension of multi criteria decision making methods in fuzzy environments, considering qualitative and quantitative criteria together and giving opportunity to make group decisions in fuzzy environments. As a result, evaluation was made based on service quality criteria for the most preferred airways companies in Turkey and these companies were ranked according to their levels of service quality.

  17. Prioritizing the performance of civil development projects in governmental administration agencies, using gray relational analysis (GRA and TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Ali Mohammadi

    2016-06-01

    Full Text Available A key indicator to evaluate the success of an organization is the degree of meeting specific civil project goals based on a predetermined schedule. Therefore, the main purpose of this paper is to evaluate the performance of governmental administration agencies based on realization of civil project goals. In this paper, the information published by the President Deputy of Strategic Planning and Control, that publishes an annual report of evaluation indicators for national civil development projects, are used to evaluate and prioritize the major and non-major governmental agencies. Also, the Gray Relational Analysis (GRA and the TOPSIS method are employed to analyze the data. The results indicate that using the GRA method, Supreme Council of Seminary and using the TOPSIS method, The Ministry of Labor and Social Affaires have gained the highest ranking.

  18. A hybrid multi-criteria decision modeling approach for the best biodiesel blend selection based on ANP-TOPSIS analysis

    Directory of Open Access Journals (Sweden)

    G. Sakthivel

    2015-03-01

    Full Text Available The ever increasing demand and depletion of fossil fuels had an adverse impact on environmental pollution. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM technique for the selection of optimum fuel blend in fish oil biodiesel for the IC engine. The proposed model, Analytical Network Process (ANP is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (in Serbian (VIKOR to evaluate the optimum blend. Evaluation of suitable blend is based on the exploratory analysis of the performance, emission and combustion parameters of the single cylinder, constant speed direct injection diesel engine at different load conditions. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS and VIKOR are used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP with TOPSIS and VIKOR. The obtained preference order of the blends for ANP-VIKOR and ANP-TOPSIS are B20 > Diesel > B40 > B60 > B80 > B100 and B20 > B40 > Diesel > B60 > B80 > B100 respectively. Hence by comparing both these methods, B20 is selected as the best blend to operate the internal combustion engines. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R& D engineers to meet the fuel economy and emission norms to empower the green revolution.

  19. New approach to solve fully fuzzy system of linear equations using ...

    Indian Academy of Sciences (India)

    Known example problems are solved to illustrate the efficacy and ... The concept of fuzzy set and fuzzy number were first introduced by Zadeh .... (iii) Fully fuzzy linear systems can be solved by linear programming approach, Gauss elim-.

  20. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    Directory of Open Access Journals (Sweden)

    Huu-Tho Nguyen

    Full Text Available Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process and a fuzzy COmplex PRoportional ASsessment (COPRAS for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  1. A Data Pre-Processing Model for the Topsis Method

    Directory of Open Access Journals (Sweden)

    Kobryń Andrzej

    2016-12-01

    Full Text Available TOPSIS is one of the most popular methods of multi-criteria decision making (MCDM. Its fundamental role is the establishment of chosen alternatives ranking based on their distance from the ideal and negative-ideal solution. There are three primary versions of the TOPSIS method distinguished: classical, interval and fuzzy, where calculation algorithms are adjusted to the character of input rating decision-making alternatives (real numbers, interval data or fuzzy numbers. Various, specialist publications present descriptions on the use of particular versions of the TOPSIS method in the decision-making process, particularly popular is the fuzzy version. However, it should be noticed, that depending on the character of accepted criteria – rating of alternatives can have a heterogeneous character. The present paper suggests the means of proceeding in the situation when the set of criteria covers characteristic criteria for each of the mentioned versions of TOPSIS, as a result of which the rating of the alternatives is vague. The calculation procedure has been illustrated by an adequate numerical example.

  2. Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment

    Directory of Open Access Journals (Sweden)

    S. Rahmani

    2016-04-01

      Conclusion: The height and electricity are of the main causes of accidents in electricity transmission and distribution industry which caused the overhead power networks to be ranked as high risk. Application of decision-making models in fuzzy environment minimizes the judgment of assessors in the risk assessment process.

  3. An intutionistic fuzzy optimization approach to vendor selection problem

    Directory of Open Access Journals (Sweden)

    Prabjot Kaur

    2016-09-01

    Full Text Available Selecting the right vendor is an important business decision made by any organization. The decision involves multiple criteria and if the objectives vary in preference and scope, then nature of decision becomes multiobjective. In this paper, a vendor selection problem has been formulated as an intutionistic fuzzy multiobjective optimization where appropriate number of vendors is to be selected and order allocated to them. The multiobjective problem includes three objectives: minimizing the net price, maximizing the quality, and maximizing the on time deliveries subject to supplier's constraints. The objection function and the demand are treated as intutionistic fuzzy sets. An intutionistic fuzzy set has its ability to handle uncertainty with additional degrees of freedom. The Intutionistic fuzzy optimization (IFO problem is converted into a crisp linear form and solved using optimization software Tora. The advantage of IFO is that they give better results than fuzzy/crisp optimization. The proposed approach is explained by a numerical example.

  4. Supplier selection problem: A fuzzy multicriteria approach

    African Journals Online (AJOL)

    kirstam

    simultaneously: maximising the total value of purchases, minimising ... Keywords: Supplier selection, multi-criteria decision-making, fuzzy logic, satisfaction ... includes both qualitative and quantitative factors, and it is necessary to make a.

  5. Fuzzy linear programming approach for solving transportation ...

    Indian Academy of Sciences (India)

    ALI EBRAHIMNEJAD

    Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran e-mail: ..... est grade of membership at x are μ ˜AL (x) and μ ˜AU (x), respectively. ..... trapezoidal fuzzy numbers transportation problem (12) are.

  6. A Fuzzy Approach to Classify Learning Disability

    OpenAIRE

    Pooja Manghirmalani; Darshana More; Kavita Jain

    2012-01-01

    The endeavor of this work is to support the special education community in their quest to be with the mainstream. The initial segment of the paper gives an exhaustive study of the different mechanisms of diagnosing learning disability. After diagnosis of learning disability the further classification of learning disability that is dyslexia, dysgraphia or dyscalculia are fuzzy. Hence the paper proposes a model based on Fuzzy Expert System which enables the classification of learning disability...

  7. A framework for evaluating the performance of automated teller machine in banking industries: A queuing model-cum-TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Christopher Osita Anyaeche

    2018-04-01

    Full Text Available The improvement in the provision of banking services to customers enhances bank’s performance (profitability and productivity and the amounts of dividend declared to shareholders as well as bank’s competitiveness. One means of fast tracking the service time for bank customers is through the use of self-servicing machines, such as automated teller machine (ATM. Total service cost, expected waiting time in queue, ATM utilization and percentage of customer loss are some of the performance indices that are used to evaluate the service rendered by a bank’s ATM. This study proposes a framework for evaluating the performance of ATM by integrating queuing model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS methodology. Applicability of the framework was tested using practical data obtained from four banks in Nigeria. It was observed that the average ATM usage in the study area was less than 50%. The TOPSIS results identified Bank A as the best ranked bank. In addition, the results obtained revealed that banks with two ATM were ranked higher than banks with more than two ATM

  8. A Novel Approach to Implement Takagi-Sugeno Fuzzy Models.

    Science.gov (United States)

    Chang, Chia-Wen; Tao, Chin-Wang

    2017-09-01

    This paper proposes new algorithms based on the fuzzy c-regressing model algorithm for Takagi-Sugeno (T-S) fuzzy modeling of the complex nonlinear systems. A fuzzy c-regression state model (FCRSM) algorithm is a T-S fuzzy model in which the functional antecedent and the state-space-model-type consequent are considered with the available input-output data. The antecedent and consequent forms of the proposed FCRSM consists mainly of two advantages: one is that the FCRSM has low computation load due to only one input variable is considered in the antecedent part; another is that the unknown system can be modeled to not only the polynomial form but also the state-space form. Moreover, the FCRSM can be extended to FCRSM-ND and FCRSM-Free algorithms. An algorithm FCRSM-ND is presented to find the T-S fuzzy state-space model of the nonlinear system when the input-output data cannot be precollected and an assumed effective controller is available. In the practical applications, the mathematical model of controller may be hard to be obtained. In this case, an online tuning algorithm, FCRSM-FREE, is designed such that the parameters of a T-S fuzzy controller and the T-S fuzzy state model of an unknown system can be online tuned simultaneously. Four numerical simulations are given to demonstrate the effectiveness of the proposed approach.

  9. Group Evidential Reasoning Approach for MADA under Fuzziness and Uncertainties

    Directory of Open Access Journals (Sweden)

    Mi Zhou

    2013-05-01

    Full Text Available Multiple attribute decision analysis (MADA problems often include both qualitative and quantitative attributes which may be either precise or inaccurate. The evidential reasoning (ER approach is one of reliable and rational methods for dealing with MADA problems and can generate aggregated assessments from a variety of attributes. In many real world decision situations, accurate assessments are difficult to provide such as in group decision situations. Extensive research in dealing with imprecise or uncertain belief structures has been conducted on the basis of the ER approach, such as interval belief degrees, interval weights and interval uncertainty. In this paper, the weights of attributes and utilities of evaluation grades are considered to be fuzzy numbers for the ER approach. Fuzzy analytic hierarchy process (FAHP is used for generating triangular fuzzy weights for attributes from a triangular fuzzy judgment matrix provided by an expert. The weighted arithmetic mean method is proposed to aggregate the triangular fuzzy weights of attributes from a group of experts. -cut is then used to transform the combined triangular fuzzy weights to interval weights for the purpose of dealing with the fuzzy type of weight and utility in a consistent way. Several pairs of group evidential reasoning based nonlinear programming models are then designed to calculate the global fuzzy belief degrees and the overall expected interval utilities of each alternative with interval weights and interval utilities as constraints. A case study is conducted to show the validity and effectiveness of the proposed approach and sensitivity analysis is also conducted on interval weights generated by different -cuts.

  10. EVALUATION OF ASSEMBLY LINE BALANCING METHODS USING AN ANALYTICAL HIERARCHY PROCESS (AHP AND TECHNIQUE FOR ORDER PREFERENCES BY SIMILARITY TO IDEAL SOLUTION (TOPSIS BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Pallavi Sharma

    2013-12-01

    Full Text Available Assembly lines are special flow-line production systems which are of great importance in the industrial production of high quantity standardized commodities. In this article, assembly line balancing problem is formulated as a multi objective (criteria problem where four easily quantifiable objectives (criteria's are defined. Objectives (criteria's included are line efficiency, balance delay, smoothness index, and line time. And the value of these objectives is calculated by five different heuristics. In this paper, focus is made on the prioritization of assembly line balancing (ALB solution methods (heuristics and to select the best of them. For this purpose, a bench mark assembly line balancing problem is solved by five different heuristics and the value of objectives criteria's (performance measures of the line is determined. Finally the prioritization of heuristics is carried out through the use of AHP-TOPSIS based approach by solving an example.

  11. Analytical fuzzy approach to biological data analysis

    Directory of Open Access Journals (Sweden)

    Weiping Zhang

    2017-03-01

    Full Text Available The assessment of the physiological state of an individual requires an objective evaluation of biological data while taking into account both measurement noise and uncertainties arising from individual factors. We suggest to represent multi-dimensional medical data by means of an optimal fuzzy membership function. A carefully designed data model is introduced in a completely deterministic framework where uncertain variables are characterized by fuzzy membership functions. The study derives the analytical expressions of fuzzy membership functions on variables of the multivariate data model by maximizing the over-uncertainties-averaged-log-membership values of data samples around an initial guess. The analytical solution lends itself to a practical modeling algorithm facilitating the data classification. The experiments performed on the heartbeat interval data of 20 subjects verified that the proposed method is competing alternative to typically used pattern recognition and machine learning algorithms.

  12. Polynomial fuzzy model-based approach for underactuated surface vessels

    DEFF Research Database (Denmark)

    Khooban, Mohammad Hassan; Vafamand, Navid; Dragicevic, Tomislav

    2018-01-01

    The main goal of this study is to introduce a new polynomial fuzzy model-based structure for a class of marine systems with non-linear and polynomial dynamics. The suggested technique relies on a polynomial Takagi–Sugeno (T–S) fuzzy modelling, a polynomial dynamic parallel distributed compensation...... surface vessel (USV). Additionally, in order to overcome the USV control challenges, including the USV un-modelled dynamics, complex nonlinear dynamics, external disturbances and parameter uncertainties, the polynomial fuzzy model representation is adopted. Moreover, the USV-based control structure...... and a sum-of-squares (SOS) decomposition. The new proposed approach is a generalisation of the standard T–S fuzzy models and linear matrix inequality which indicated its effectiveness in decreasing the tracking time and increasing the efficiency of the robust tracking control problem for an underactuated...

  13. Fuzzy set approach to quality function deployment: An investigation

    Science.gov (United States)

    Masud, Abu S. M.

    1992-01-01

    The final report of the 1992 NASA/ASEE Summer Faculty Fellowship at the Space Exploration Initiative Office (SEIO) in Langley Research Center is presented. Quality Function Deployment (QFD) is a process, focused on facilitating the integration of the customer's voice in the design and development of a product or service. Various input, in the form of judgements and evaluations, are required during the QFD analyses. All the input variables in these analyses are treated as numeric variables. The purpose of the research was to investigate how QFD analyses can be performed when some or all of the input variables are treated as linguistic variables with values expressed as fuzzy numbers. The reason for this consideration is that human judgement, perception, and cognition are often ambiguous and are better represented as fuzzy numbers. Two approaches for using fuzzy sets in QFD have been proposed. In both cases, all the input variables are considered as linguistic variables with values indicated as linguistic expressions. These expressions are then converted to fuzzy numbers. The difference between the two approaches is due to how the QFD computations are performed with these fuzzy numbers. In Approach 1, the fuzzy numbers are first converted to their equivalent crisp scores and then the QFD computations are performed using these crisp scores. As a result, the output of this approach are crisp numbers, similar to those in traditional QFD. In Approach 2, all the QFD computations are performed with the fuzzy numbers and the output are fuzzy numbers also. Both the approaches have been explained with the help of illustrative examples of QFD application. Approach 2 has also been applied in a QFD application exercise in SEIO, involving a 'mini moon rover' design. The mini moon rover is a proposed tele-operated vehicle that will traverse and perform various tasks, including autonomous operations, on the moon surface. The output of the moon rover application exercise is a

  14. Improvements to Earthquake Location with a Fuzzy Logic Approach

    Science.gov (United States)

    Gökalp, Hüseyin

    2018-01-01

    In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

  15. A logical approach to fuzzy truth hedges

    Czech Academy of Sciences Publication Activity Database

    Esteva, F.; Godo, L.; Noguera, Carles

    2013-01-01

    Roč. 232, č. 1 (2013), s. 366-385 ISSN 0020-0255 Institutional support: RVO:67985556 Keywords : Mathematical fuzzy logic * Standard completeness * Truth hedges Subject RIV: BA - General Mathematics Impact factor: 3.893, year: 2013 http://library.utia.cas.cz/separaty/2016/MTR/noguera-0469148.pdf

  16. Empirical Bayes Approaches to Multivariate Fuzzy Partitions.

    Science.gov (United States)

    Woodbury, Max A.; Manton, Kenneth G.

    1991-01-01

    An empirical Bayes-maximum likelihood estimation procedure is presented for the application of fuzzy partition models in describing high dimensional discrete response data. The model describes individuals in terms of partial membership in multiple latent categories that represent bounded discrete spaces. (SLD)

  17. A fuzzy behaviorist approach to sensor-based robot control

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.

    1996-05-01

    Sensor-based operation of autonomous robots in unstructured and/or outdoor environments has revealed to be an extremely challenging problem, mainly because of the difficulties encountered when attempting to represent the many uncertainties which are always present in the real world. These uncertainties are primarily due to sensor imprecisions and unpredictability of the environment, i.e., lack of full knowledge of the environment characteristics and dynamics. An approach. which we have named the {open_quotes}Fuzzy Behaviorist Approach{close_quotes} (FBA) is proposed in an attempt to remedy some of these difficulties. This approach is based on the representation of the system`s uncertainties using Fuzzy Set Theory-based approximations and on the representation of the reasoning and control schemes as sets of elemental behaviors. Using the FBA, a formalism for rule base development and an automated generator of fuzzy rules have been developed. This automated system can automatically construct the set of membership functions corresponding to fuzzy behaviors. Once these have been expressed in qualitative terms by the user. The system also checks for completeness of the rule base and for non-redundancy of the rules (which has traditionally been a major hurdle in rule base development). Two major conceptual features, the suppression and inhibition mechanisms which allow to express a dominance between behaviors are discussed in detail. Some experimental results obtained with the automated fuzzy, rule generator applied to the domain of sensor-based navigation in aprion unknown environments. using one of our autonomous test-bed robots as well as a real car in outdoor environments, are then reviewed and discussed to illustrate the feasibility of large-scale automatic fuzzy rule generation using the {open_quotes}Fuzzy Behaviorist{close_quotes} concepts.

  18. A combined technique using SEM and TOPSIS for the commercialization capability of R&D project evaluation

    Directory of Open Access Journals (Sweden)

    Charttirot Karaveg

    2015-07-01

    Full Text Available There is a high risk of R&D based innovation being commercialized, especially in the innovation transfer process which is a concern to many entrepreneurs and researchers. The purpose of this research is to develop the criteria of R&D commercialization capability and to propose a combined technique of Structural Equation Modelling (SEM and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS for R&D project evaluation. The research utilized a mixed-method approach. The first phase comprised a qualitative study on commercialization criteria development though the survey research of 272 successful entrepreneurs and researchers in all industrial sectors in Thailand. The data was collected with a structured questionnaire and analyzed by SEM. The second phase was involved with SEM-TOPSIS technique development and a case study of 45 R&D projects in research institutes and incubators for technique validation. The research results reveal that there were six criteria for R&D project commercialization capability, these are arranged according to the significance; marketing, technology, finance, non-financial impact, intellectual property, and human resource. The holistic criteria is presented in decreasing order on the ambiguous subjectivity of the fuzzy-expert system, to help with effectively funding R&D and to prevent a resource meltdown. This study applies SEM to the relative weighting of hierarchical criteria. The TOPSIS approach is employed to rank the alternative performance. An integrated SEM-TOPSIS is proposed for the first time and applied to present R&D projects shown to be effective and feasible in evaluating R&D commercialization capacity.

  19. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  20. A fuzzy approach for modelling radionuclide in lake system

    International Nuclear Information System (INIS)

    Desai, H.K.; Christian, R.A.; Banerjee, J.; Patra, A.K.

    2013-01-01

    Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of 3 H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict 3 H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and 3 H concentration at discharge point. The Output was 3 H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. -- Highlights: • Uncommon approach (Fuzzy Rule Base) of modelling radionuclide dispersion in Lake. • Predicts 3 H released from Kakrapar Atomic Power Station at a point of human exposure. • RMSE of fuzzy model is 1.95, which means, it has well imitated natural ecosystem

  1. Stock and option portfolio using fuzzy logic approach

    Science.gov (United States)

    Sumarti, Novriana; Wahyudi, Nanang

    2014-03-01

    Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

  2. Uncovering transcriptional interactions via an adaptive fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Chen Chung-Ming

    2009-12-01

    Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

  3. An improved advertising CTR prediction approach based on the fuzzy deep neural network.

    Science.gov (United States)

    Jiang, Zilong; Gao, Shu; Li, Mingjiang

    2018-01-01

    Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise.

  4. Consumer preference models: fuzzy theory approach

    Science.gov (United States)

    Turksen, I. B.; Wilson, I. A.

    1993-12-01

    Consumer preference models are widely used in new product design, marketing management, pricing and market segmentation. The purpose of this article is to develop and test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation) and how much to make (market share prediction).

  5. Analyzing the drivers of green manufacturing with fuzzy approach

    DEFF Research Database (Denmark)

    Govindan, Kannan; Diabat, Ali; Madan Shankar, K.

    2015-01-01

    India, and aided by their replies; a pair-wise comparison was made among the drivers. The pair-wise comparison is used as an input data and the drivers were analyzed on its basis. The analysis resorted to the use of a fuzzy Multi Criteria Decision Making (MCDM) approach. The obtained results...

  6. Fuzzy approach for short term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Chenthur Pandian, S.; Duraiswamy, K.; Kanagaraj, N. [Electrical and Electronics Engg., K.S. Rangasamy College of Technology, Tiruchengode 637209, Tamil Nadu (India); Christober Asir Rajan, C. [Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Pondicherry (India)

    2006-04-15

    The main objective of short term load forecasting (STLF) is to provide load predictions for generation scheduling, economic load dispatch and security assessment at any time. The STLF is needed to supply necessary information for the system management of day-to-day operations and unit commitment. In this paper, the 'time' and 'temperature' of the day are taken as inputs for the fuzzy logic controller and the 'forecasted load' is the output. The input variable 'time' has been divided into eight triangular membership functions. The membership functions are Mid Night, Dawn, Morning, Fore Noon, After Noon, Evening, Dusk and Night. Another input variable 'temperature' has been divided into four triangular membership functions. They are Below Normal, Normal, Above Normal and High. The 'forecasted load' as output has been divided into eight triangular membership functions. They are Very Low, Low, Sub Normal, Moderate Normal, Normal, Above Normal, High and Very High. Case studies have been carried out for the Neyveli Thermal Power Station Unit-II (NTPS-II) in India. The fuzzy forecasted load values are compared with the conventional forecasted values. The forecasted load closely matches the actual one within +/-3%. (author)

  7. A fuzzy approach for modelling radionuclide in lake system.

    Science.gov (United States)

    Desai, H K; Christian, R A; Banerjee, J; Patra, A K

    2013-10-01

    Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of (3)H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict (3)H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and (3)H concentration at discharge point. The Output was (3)H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. A fuzzy AHP approach for employee recruitment

    Directory of Open Access Journals (Sweden)

    Mohsen Varmazyar

    2014-01-01

    Full Text Available Human resource management plays an essential role on development of any business organization. Selection of employee normally depends on various criteria such as employee commitment, necessary skills, etc. Therefore, a good strategy to hire appropriate employee is a multi-criteria decision making (MCDM specially the ones, which could handle uncertainty, properly. In this paper, we present a method to use MCDM techniques for hiring employees. In fact, the present work proposes a Fuzzy Analytic Hierarchy Process (FAHP as one of the most popular multi-criteria decision making techniques. A computer application is developed where it receives the configuration of the employee selection problem, evaluates the candidates and ranks them using the appropriate voting system.

  9. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    Science.gov (United States)

    Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

    2007-10-01

    Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

  10. A Fuzzy Multi-Criteria SWOT Analysis: An Application to Nuclear Power Plant Site Selection

    Directory of Open Access Journals (Sweden)

    Mehmet Ekmekcioglu

    2011-08-01

    Full Text Available SWOT (Strengths, Weaknesses, Opportunities and Threats analysis is a commonly used and an important technique for analyzing internal and external environments in order to provide a systematic approach and support for a decision making. SWOT is criticized mostly for considering only qualitative examination of environmental factors, no priority for various factors and strategies, and no vagueness of the factors under fuzziness. In this paper, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution integrated with fuzzy AHP (Analytical Hierarchy Process is used to develop fuzzy multi-criteria SWOT analysis in order to overcome these shortcomings. Nuclear power plant site selection, which is a strategic and important issue for Turkeyrs energy policy making, is considered as an application case study that demonstrated the applicability of the developed fuzzy SWOT model.

  11. Generalized coherent state approach to star products and applications to the fuzzy sphere

    International Nuclear Information System (INIS)

    Alexanian, G.; Pinzul, A.; Stern, A.

    2001-01-01

    We construct a star product associated with an arbitrary two-dimensional Poisson structure using generalized coherent states on the complex plane. From our approach one easily recovers the star product for the fuzzy torus, and also one for the fuzzy sphere. For the latter we need to define the 'fuzzy' stereographic projection to the plane and the fuzzy sphere integration measure, which in the commutative limit reduce to the usual formulae for the sphere

  12. Hybrid Multicriteria Group Decision Making Method for Information System Project Selection Based on Intuitionistic Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Jian Guo

    2013-01-01

    Full Text Available Information system (IS project selection is of critical importance to every organization in dynamic competing environment. The aim of this paper is to develop a hybrid multicriteria group decision making approach based on intuitionistic fuzzy theory for IS project selection. The decision makers’ assessment information can be expressed in the form of real numbers, interval-valued numbers, linguistic variables, and intuitionistic fuzzy numbers (IFNs. All these evaluation pieces of information can be transformed to the form of IFNs. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate IS project in group decision making environment. Finally, a numerical example for information system projects selection is given to illustrate application of hybrid multi-criteria group decision making (MCGDM method based on intuitionistic fuzzy theory and TOPSIS method.

  13. A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

    Directory of Open Access Journals (Sweden)

    Ozge Cagcag Yolcu

    2013-01-01

    Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

  14. Fuzzy Approaches to Flexible Querying in XML Retrieval

    Directory of Open Access Journals (Sweden)

    Stefania Marrara

    2016-04-01

    Full Text Available In this paper we review some approaches to flexible querying in XML that apply several techniques among which Fuzzy Set Theory. In particular we focus on FleXy, a flexible extension of XQuery-FT that was developed as a library on the open source engine Base-X. We then present PatentLight, a tool for patent retrieval that was developed to show the expressive power of Flexy.

  15. Human motion sensing and recognition a fuzzy qualitative approach

    CERN Document Server

    Liu, Honghai; Ji, Xiaofei; Chan, Chee Seng; Khoury, Mehdi

    2017-01-01

    This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the ...

  16. COMPARISION OF FUZZY PERT APPROACHES IN MACHINE PRODUCTION PROCESS

    Directory of Open Access Journals (Sweden)

    İRFAN ERTUĞRUL

    2013-06-01

    Full Text Available In traditional PERT (Program Evaluation and Review Technique activity durations are represented as crisp numbers and assumed that they are drawn from beta distribution. However, in real life the duration of the activities are usually difficult to estimate precisely.  In order to overcome this difficulty, there are studies in the literature that combine fuzzy set theory and PERT method. In this study, two fuzzy PERT approaches proposed by different authors are employed to find the degrees of criticality of each path in the network and comparison of these two methods is also given. Furthermore, by the help of these methods the criticality of the activities in the marble machine production process of a company that manufactures machinery is determined and results are compared.

  17. A NEW APPROACH ON SHORTEST PATH IN FUZZY ENVIRONMENT

    OpenAIRE

    A. Nagoorgani; A. Mumtaj Begam

    2010-01-01

    This paper introduces a new type of fuzzy shortest path network problem using triangular fuzzy number. To find the smallest edge by the fuzzy distance using graded mean integration representation of generalized fuzzy number for every node. Thus the optimum shortest path for the given problem is obtained.

  18. A neuro approach to solve fuzzy Riccati differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Shahrir, Mohammad Shazri, E-mail: mshazri@gmail.com [InstitutSainsMatematik, Universiti Malaya 50603 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur (Malaysia); Telekom Malaysia, R& D TM Innovation Centre, LingkaranTeknokrat Timur, 63000 Cyberjaya, Selangor (Malaysia); Kumaresan, N., E-mail: drnk2008@gmail.com; Kamali, M. Z. M.; Ratnavelu, Kurunathan [InstitutSainsMatematik, Universiti Malaya 50603 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur (Malaysia)

    2015-10-22

    There are many applications of optimal control theory especially in the area of control systems in engineering. In this paper, fuzzy quadratic Riccati differential equation is estimated using neural networks (NN). Previous works have shown reliable results using Runge-Kutta 4th order (RK4). The solution can be achieved by solving the 1st Order Non-linear Differential Equation (ODE) that is found commonly in Riccati differential equation. Research has shown improved results relatively to the RK4 method. It can be said that NN approach shows promising results with the advantage of continuous estimation and improved accuracy that can be produced over RK4.

  19. New approach for solving intuitionistic fuzzy multi-objective ...

    Indian Academy of Sciences (India)

    SANKAR KUMAR ROY

    2018-02-07

    Feb 7, 2018 ... Transportation problem; multi-objective decision making; intuitionistic fuzzy programming; interval programming ... MOTP under multi-choice environment using utility func- ... theory is an intuitionistic fuzzy set (IFS), which was.

  20. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  1. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    International Nuclear Information System (INIS)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young; Sang, Seok Yoon

    2014-01-01

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  2. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Sang, Seok Yoon [Engineering and Technical Center, Korea Hydro, Daejeon (Korea, Republic of)

    2014-08-15

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  3. Logistics Service Provider Selection through an Integrated Fuzzy Multicriteria Decision Making Approach

    OpenAIRE

    Gülşen Akman; Kasım Baynal

    2014-01-01

    Nowadays, the demand of third-party logistics provider becomes an increasingly important issue for companies to improve their customer service and to decrease logistics costs. This paper presents an integrated fuzzy approach for the evaluation and selection of 3rd party logistics service providers. This method consists of two techniques: (1) use fuzzy analytic hierarchy process to identify weights of evaluation criteria; (2) apply fuzzy technique for order preference by similarity to ideal so...

  4. H∞ Control of Polynomial Fuzzy Systems: A Sum of Squares Approach

    OpenAIRE

    Bomo W. Sanjaya; Bambang Riyanto Trilaksono; Arief Syaichu-Rohman

    2014-01-01

    This paper proposes the control design ofa nonlinear polynomial fuzzy system with H∞ performance objective using a sum of squares (SOS) approach. Fuzzy model and controller are represented by a polynomial fuzzy model and controller. The design condition is obtained by using polynomial Lyapunov functions that not only guarantee stability but also satisfy the H∞ performance objective. The design condition is represented in terms of an SOS that can be numerically solved via the SOSTOOLS. A simul...

  5. Development of erosion risk map using fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Fauzi Manyuk

    2017-01-01

    Full Text Available Erosion-hazard assessment is an important aspect in the management of a river basin such as Siak River Basin, Riau Province, Indonesia. This study presents an application of fuzzy logic approach to develop erosion risk map based on geographic information system. Fuzzy logic is a computing approach based on “degrees of truth” rather than the usual “true or false” (1 or 0 Boolean logic on which the modern computer is based. The results of the erosion risk map were verified by using field measurements. The verification result shows that the parameter of soil-erodibility (K indicates a good agreement with field measurement data. The classification of soil-erodibility (K as the result of validation were: very low (0.0–0.1, medium (0.21-0.32, high (0.44-0.55 and very high (0.56-0.64. The results obtained from this study show that the erosion risk map of Siak River Basin were dominantly classified as medium level which cover about 68.54%. The other classifications were high and very low erosion level which cover about 28.84% and 2.61% respectively.

  6. A Grey Fuzzy Logic Approach for Cotton Fibre Selection

    Science.gov (United States)

    Chakraborty, Shankar; Das, Partha Protim; Kumar, Vidyapati

    2017-06-01

    It is a well known fact that the quality of ring spun yarn predominantly depends on various physical properties of cotton fibre. Any variation in these fibre properties may affect the strength and unevenness of the final yarn. Thus, so as to achieve the desired yarn quality and characteristics, it becomes imperative for the spinning industry personnel to identify the most suitable cotton fibre from a set of feasible alternatives in presence of several conflicting properties/attributes. This cotton fibre selection process can be modelled as a Multi-Criteria Decision Making (MCDM) problem. In this paper, a grey fuzzy logic-based approach is proposed for selection of the most apposite cotton fibre from 17 alternatives evaluated based on six important fibre properties. It is observed that the preference order of the top-ranked cotton fibres derived using the grey fuzzy logic approach closely matches with that attained by the past researchers which proves the application potentiality of this method in solving varying MCDM problems in textile industries.

  7. Application of ANNs approach for solving fully fuzzy polynomials system

    Directory of Open Access Journals (Sweden)

    R. Novin

    2017-11-01

    Full Text Available In processing indecisive or unclear information, the advantages of fuzzy logic and neurocomputing disciplines should be taken into account and combined by fuzzy neural networks. The current research intends to present a fuzzy modeling method using multi-layer fuzzy neural networks for solving a fully fuzzy polynomials system. To clarify the point, it is necessary to inform that a supervised gradient descent-based learning law is employed. The feasibility of the method is examined using computer simulations on a numerical example. The experimental results obtained from the investigation of the proposed method are valid and delivers very good approximation results.

  8. Diagnosis of Feedwater Heater Performance Degradation using Fuzzy Approach

    International Nuclear Information System (INIS)

    Kim, Hyeonmin; Kang, Yeon Kwan; Heo, Gyunyoung; Song, Seok Yoon

    2014-01-01

    It is inevitable to avoid degradation of component, which operates continuously for long time in harsh environment. Since this degradation causes economical loss and human loss, it is important to monitor and diagnose the degradation of component. The diagnosis requires a well-systematic method for timely decision. Before this article, the methods using regression model and diagnosis table have been proposed to perform the diagnosis study for thermal efficiency in Nuclear Power Plants (NPPs). Since the regression model was numerically less-stable under changes of operating variables, it was difficult to provide good results in operating plants. Contrary to this, the diagnosis table was hard to use due to ambiguous points and to detect how it affects degradation. In order to cover the issues of previous researches, we proposed fuzzy approaches and applied it to diagnose Feedwater Heater (FWH) degradation to check the feasibility. The degradation of FWHs is not easy to be observed, while trouble such as tube leakage may bring simultaneous damage to the tube bundle. This study explains the steps of diagnosing typical failure modes of FWHs. In order to cover the technical issues of previous researches, we adopted fuzzy logic to suggest a diagnosis algorithm for the degradation of FHWs and performed feasibility study. In this paper, total 7 modes of FWH degradation modes are considered, which are High Drain Level, Low Shell Pressure, Tube Pressure Increase, Tube Fouling, Pass Partition Plate Leakage, Tube Leakage, Abnormal venting. From the literature survey and simulation, diagnosis table for FWH is made. We apply fuzzy logic based on diagnosis table. Authors verify fuzzy diagnosis for FWH degradation synthesized the random input sets from made diagnosis table. Comparing previous researches, suggested method more-stable under changes of operating variables, than regression model. On the contrary, the problem which ambiguous points and detect how it affects degradation

  9. Diagnosis of Feedwater Heater Performance Degradation using Fuzzy Approach

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeonmin; Kang, Yeon Kwan; Heo, Gyunyoung [Kyung Hee Univ., Yongin (Korea, Republic of); Song, Seok Yoon [Korea Hydro and Nuclear Power, Daejeon (Korea, Republic of)

    2014-05-15

    It is inevitable to avoid degradation of component, which operates continuously for long time in harsh environment. Since this degradation causes economical loss and human loss, it is important to monitor and diagnose the degradation of component. The diagnosis requires a well-systematic method for timely decision. Before this article, the methods using regression model and diagnosis table have been proposed to perform the diagnosis study for thermal efficiency in Nuclear Power Plants (NPPs). Since the regression model was numerically less-stable under changes of operating variables, it was difficult to provide good results in operating plants. Contrary to this, the diagnosis table was hard to use due to ambiguous points and to detect how it affects degradation. In order to cover the issues of previous researches, we proposed fuzzy approaches and applied it to diagnose Feedwater Heater (FWH) degradation to check the feasibility. The degradation of FWHs is not easy to be observed, while trouble such as tube leakage may bring simultaneous damage to the tube bundle. This study explains the steps of diagnosing typical failure modes of FWHs. In order to cover the technical issues of previous researches, we adopted fuzzy logic to suggest a diagnosis algorithm for the degradation of FHWs and performed feasibility study. In this paper, total 7 modes of FWH degradation modes are considered, which are High Drain Level, Low Shell Pressure, Tube Pressure Increase, Tube Fouling, Pass Partition Plate Leakage, Tube Leakage, Abnormal venting. From the literature survey and simulation, diagnosis table for FWH is made. We apply fuzzy logic based on diagnosis table. Authors verify fuzzy diagnosis for FWH degradation synthesized the random input sets from made diagnosis table. Comparing previous researches, suggested method more-stable under changes of operating variables, than regression model. On the contrary, the problem which ambiguous points and detect how it affects degradation

  10. H∞ Control of Polynomial Fuzzy Systems: A Sum of Squares Approach

    Directory of Open Access Journals (Sweden)

    Bomo W. Sanjaya

    2014-07-01

    Full Text Available This paper proposes the control design ofa nonlinear polynomial fuzzy system with H∞ performance objective using a sum of squares (SOS approach. Fuzzy model and controller are represented by a polynomial fuzzy model and controller. The design condition is obtained by using polynomial Lyapunov functions that not only guarantee stability but also satisfy the H∞ performance objective. The design condition is represented in terms of an SOS that can be numerically solved via the SOSTOOLS. A simulation study is presented to show the effectiveness of the SOS-based H∞ control designfor nonlinear polynomial fuzzy systems.

  11. A Fuzzy MCDM Approach to Evaluate Green Suppliers

    Directory of Open Access Journals (Sweden)

    Gizem Cifci

    2011-10-01

    Full Text Available Nowadays the effect of industrial production on the environment brought out the importance of the green concept in supply chains. Particularly for supplier firms, greening is essential in a supply chain because with growing worldwide awareness of environmental protection, green production has become an important theme for almost every manufacturer. While literature related to supplier evaluation is plentiful, the works on green supplier evaluation are rather limited. Therefore, a green supplier evaluation model is proposed in this study. Due to its multi-criteria nature, the green supplier evaluation process requires an appropriate multi criteria analysis and solution approach. Selecting a proper method involves an insight analysis among available multi-criteria decision making (MCDM techniques. Among numerous methods of MCDM, this paper presents a decision framework based on group decision making (GDM and fuzzy analytic hierarchy process (FAHP for evaluating and selecting green suppliers. The applicability of the proposed approach is verified through a case study.

  12. Evaluation of Green IT services with Fuzzy Screening approach

    Directory of Open Access Journals (Sweden)

    Sajjad Shokouhyar‎

    2017-11-01

    Full Text Available Regarding development of Information Technology, the world of industry has inordinately benefited, albeit that has some losses. Unless the losses are considered, advanced losses will be seen after progress with which is more difficult to cope. Neglecting the future and the risk involved in the industry, not to mention the lack of knowledge in dealing with sudden alterations, compel irrecoverable loss. In this context, information technology services in organizations are aimed to be cost-effective and have minimum environmental impact, according to green information technology strategies. Concerning significance of the issue, purpose of this research is assessment of information technology services with respect to greenness level in a general contractor organization by combination of Fuzzy Analytic Hierarchy Process and Fuzzy Screening Procedure to enhance the greenness level of IT services. The effectiveness of using this approach is including qualitative, quantitative, and uncertainty nature of the problem. In this paper, to consider the Green IT services criteria, literatures have been studied by meta-synthesis method, then the importance of the criteria has been determined by questionnaires so as to rank Green IT criteria. Eventually, the organization level has been concluded in terms of the greenness level of IT services. As a case study, IT experts and managers of KAYSON Inc. organization are considered as statistical population of this research. The reduction had the highest weight among other criteria- recycling and reusing - in KAYSON Inc. organization. Finally, the organization greenness level was determined moderate in terms of IT services.

  13. Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering: Application to Medical Image MRI

    Directory of Open Access Journals (Sweden)

    Nour-Eddine El Harchaoui

    2013-01-01

    Full Text Available The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems of uncertain data in complex systems. We used the membership function of fuzzy c-means (FCM to initialize the parameters of possibilistic c-means (PCM, in order to solve the problem of coinciding clusters that are generated by PCM and also overcome the weakness of FCM to noise. To validate our approach, we used several validity indexes and we compared them with other conventional classification algorithms: fuzzy c-means, possibilistic c-means, and possibilistic fuzzy c-means. The experiments were realized on different synthetics data sets and real brain MR images.

  14. A Compensatory Approach to Multiobjective Linear Transportation Problem with Fuzzy Cost Coefficients

    Directory of Open Access Journals (Sweden)

    Hale Gonce Kocken

    2011-01-01

    Full Text Available This paper deals with the Multiobjective Linear Transportation Problem that has fuzzy cost coefficients. In the solution procedure, many objectives may conflict with each other; therefore decision-making process becomes complicated. And also due to the fuzziness in the costs, this problem has a nonlinear structure. In this paper, fuzziness in the objective functions is handled with a fuzzy programming technique in the sense of multiobjective approach. And then we present a compensatory approach to solve Multiobjective Linear Transportation Problem with fuzzy cost coefficients by using Werner's and operator. Our approach generates compromise solutions which are both compensatory and Pareto optimal. A numerical example has been provided to illustrate the problem.

  15. A TSK neuro-fuzzy approach for modeling highly dynamic systems

    NARCIS (Netherlands)

    Acampora, G.

    2011-01-01

    This paper introduces a new type of TSK-based neuro-fuzzy approach and its application to modeling highly dynamic systems. In details, our proposal performs an adaptive supervised learning on a collection of time series in order to create a so-called Timed Automata Based Fuzzy Controller, i.e. an

  16. A systematic approach for fine-tuning of fuzzy controllers applied to WWTPs

    DEFF Research Database (Denmark)

    Ruano, M.V.; Ribes, J.; Sin, Gürkan

    2010-01-01

    A systematic approach for fine-tuning fuzzy controllers has been developed and evaluated for an aeration control system implemented in a WWTR The challenge with the application of fuzzy controllers to WWTPs is simply that they contain many parameters, which need to be adjusted for different WWTP ...

  17. Fuzzy Axiomatic Design approach based green supplier selection

    DEFF Research Database (Denmark)

    Kannan, Devika; Govindan, Kannan; Rajendran, Sivakumar

    2015-01-01

    proposes a multi-criteria decision-making (MCDM) approach called Fuzzy Axiomatic Design (FAD) to select the best green supplier for Singapore-based plastic manufacturing company. At first, the environmental criteria was developed along with the traditional criteria based on the literature review......Abstract Green Supply Chain Management (GSCM) is a developing concept recently utilized by manufacturing firms of all sizes. All industries, small or large, seek improvements in the purchasing of raw materials, manufacturing, allocation, transportation efficiency, in curbing storage time, importing...... responsible in addition to being efficiently managed. A significant way to implement responsible GSCM is to reconsider, in innovative ways, the purchase and supply cycle, and a preliminary step would be to ensure that the supplier of goods successfully incorporates green criteria. Therefore, this paper...

  18. A FUZZY MULTICRITERIA APPROACH FOR IT GOVERNANCE EVALUATION

    Directory of Open Access Journals (Sweden)

    Angel Cobo

    2014-10-01

    Full Text Available This work seeks to provide a new multi-criteria approach to assess IT Governance (ITG in the area of Strategic Alignment. The complete methodological development process is described. The evaluation model uses Fuzzy Analytic Hierarchy Process (FAHP and it is targeted to IT processes, more specifically to the COBIT© IT maturity levels, domains and processes, thus providing a differentiated analysis of importance for each item. Its relevance is related to addressing isolated and individual evaluation criteria that are normally practiced in audits of processes. The model allows generating information that extends the guarantees of compliance and corporate governance from different organizations. This research demonstrates that the combined use of multi-criteria decision methodologies and soft computing proves to be particularly suitable for Strategic Alignment such as the focal area of COBIT. The model was applied in a big retail Brazilian company.

  19. Fuzzy Gauge Capability (Cg and Cgk) through Buckley Approach

    OpenAIRE

    Seyed Habib A. Rahmati; Mohsen Sadegh Amalnick

    2015-01-01

    Different terms of the Statistical Process Control (SPC) has sketch in the fuzzy environment. However, Measurement System Analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works b...

  20. An approach to solve replacement problems under intuitionistic fuzzy nature

    Science.gov (United States)

    Balaganesan, M.; Ganesan, K.

    2018-04-01

    Due to impreciseness to solve the day to day problems the researchers use fuzzy sets in their discussions of the replacement problems. The aim of this paper is to solve the replacement theory problems with triangular intuitionistic fuzzy numbers. An effective methodology based on fuzziness index and location index is proposed to determine the optimal solution of the replacement problem. A numerical example is illustrated to validate the proposed method.

  1. An Extended TOPSIS Method for the Multiple Attribute Decision Making Problems Based on Interval Neutrosophic Set

    Directory of Open Access Journals (Sweden)

    Pingping Chi

    2013-03-01

    Full Text Available The interval neutrosophic set (INS can be easier to express the incomplete, indeterminate and inconsistent information, and TOPSIS is one of the most commonly used and effective method for multiple attribute decision making, however, in general, it can only process the attribute values with crisp numbers. In this paper, we have extended TOPSIS to INS, and with respect to the multiple attribute decision making problems in which the attribute weights are unknown and the attribute values take the form of INSs, we proposed an expanded TOPSIS method. Firstly, the definition of INS and the operational laws are given, and distance between INSs is defined. Then, the attribute weights are determined based on the Maximizing deviation method and an extended TOPSIS method is developed to rank the alternatives. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

  2. Development of a noise prediction model based on advanced fuzzy approaches in typical industrial workrooms.

    Science.gov (United States)

    Aliabadi, Mohsen; Golmohammadi, Rostam; Khotanlou, Hassan; Mansoorizadeh, Muharram; Salarpour, Amir

    2014-01-01

    Noise prediction is considered to be the best method for evaluating cost-preventative noise controls in industrial workrooms. One of the most important issues is the development of accurate models for analysis of the complex relationships among acoustic features affecting noise level in workrooms. In this study, advanced fuzzy approaches were employed to develop relatively accurate models for predicting noise in noisy industrial workrooms. The data were collected from 60 industrial embroidery workrooms in the Khorasan Province, East of Iran. The main acoustic and embroidery process features that influence the noise were used to develop prediction models using MATLAB software. Multiple regression technique was also employed and its results were compared with those of fuzzy approaches. Prediction errors of all prediction models based on fuzzy approaches were within the acceptable level (lower than one dB). However, Neuro-fuzzy model (RMSE=0.53dB and R2=0.88) could slightly improve the accuracy of noise prediction compared with generate fuzzy model. Moreover, fuzzy approaches provided more accurate predictions than did regression technique. The developed models based on fuzzy approaches as useful prediction tools give professionals the opportunity to have an optimum decision about the effectiveness of acoustic treatment scenarios in embroidery workrooms.

  3. Preference uncertainty in nonmarket valuation: a fuzzy approach

    NARCIS (Netherlands)

    Kooten, van G.C.; Krcmar, E.; Bulte, E.H.

    2001-01-01

    In this article, we consider uncertain preferences for non-market goods, but we move away from a probabilistic representation of uncertainty and propose the use of fuzzy contingent valuation. We assume that a decision maker never fully knows her own utility function and we treat utility as a fuzzy

  4. A Fuzzy Linear Programming Approach for Aggregate Production Planning

    DEFF Research Database (Denmark)

    Iris, Cagatay; Cevikcan, Emre

    2014-01-01

    a mathematical programming framework for aggregate production planning problem under imprecise data environment. After providing background information about APP problem, together with fuzzy linear programming, the fuzzy linear programming model of APP is solved on an illustrative example for different a...

  5. Analytic Model Predictive Control of Uncertain Nonlinear Systems: A Fuzzy Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Xiuyan Peng

    2015-01-01

    Full Text Available A fuzzy adaptive analytic model predictive control method is proposed in this paper for a class of uncertain nonlinear systems. Specifically, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved. Then, recurring to analytic model predictive control law, combined with fuzzy adaptive approach, the fuzzy adaptive predictive controller synthesis for the underlying systems is developed. To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system, the robust compensation term is introduced. It is shown that by applying the fuzzy adaptive analytic model predictive controller the rudder roll stabilization system is ultimately uniformly bounded stabilized in the H-infinity sense. Finally, simulation results demonstrate the effectiveness of the proposed method.

  6. Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

    Directory of Open Access Journals (Sweden)

    Daniel Osezua Aikhuele

    2017-09-01

    Full Text Available This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS model. The integrated model which uses the improved score func-tion and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for eval-uating and selecting some design related problems including a real-life case study for the selec-tion of the best concept design for a new printed-circuit-board (PCB and for a hypothetical ex-ample. The model which provides a novel alternative, has been compared with similar computa-tional methods in the literature.

  7. Optimizing Concurrent M3-Transactions: A Fuzzy Constraint Satisfaction Approach

    Directory of Open Access Journals (Sweden)

    Peng LI

    2004-10-01

    Full Text Available Due to the high connectivity and great convenience, many E-commerce application systems have a high transaction volume. Consequently, the system state changes rapidly and it is likely that customers issue transactions based on out-of-date state information. Thus, the potential of transaction abortion increases greatly. To address this problem, we proposed an M3-transaction model. An M3-transaction is a generalized transaction where users can issue their preferences in a request by specifying multiple criteria and optional data resources simultaneously within one transaction. In this paper, we introduce the transaction grouping and group evaluation techniques. We consider evaluating a group of M3-transactions arrived to the system within a short duration together. The system makes optimal decisions in allocating data to transactions to achieve better customer satisfaction and lower transaction failure rate. We apply the fuzzy constraint satisfaction approach for decision-making. We also conduct experimental studies to evaluate the performance of our approach. The results show that the M3-transaction with group evaluation is more resilient to failure and yields much better performance than the traditional transaction model.

  8. Investigation of the potential of fuzzy sets and related approaches for treating uncertainties in radionuclide transfer predictions

    International Nuclear Information System (INIS)

    Shaw, W.; Grindrod, P.

    1989-01-01

    This document encompasses two main items. The first consists of a review of four aspects of fuzzy sets, namely, the general framework, the role of expert judgment, mathematical and computational aspects, and present applications. The second consists of the application of fuzzy-set theory to simplified problems in radionuclide migration, with comparisons between fuzzy and probabilistic approaches, treated both analytically and computationally. A new approach to fuzzy differential equations is presented, and applied to simple ordinary and partial differential equations. It is argued that such fuzzy techniques represent a viable alternative to probabilistic risk assessment, for handling systems subject to uncertainties

  9. Developing a univariate approach to phase-I monitoring of fuzzy quality profiles

    Directory of Open Access Journals (Sweden)

    Kazem Noghondarian

    2012-10-01

    Full Text Available In many real-world applications, the quality of a process or a particular product can be characterized by a functional relationship called profile. A profile builds the relationships between a response quality characteristic and one or more explanatory variables. Monitoring the quality of a profile is implemented to understand and to verify the stability of this functional relationship over time. In some real applications, a fuzzy linear regression model can represent the profile adequately where the response quality characteristic is fuzzy. The purpose of this paper is to develop an approach for monitoring process/product profiles in fuzzy environment. A model in fuzzy linear regression is developed to construct the quality profiles by using linear programming and then fuzzy individuals and moving-range (I-MR control charts are developed to monitor both intercept and slope of fuzzy profiles to achieve an in-control process. A case study in customer satisfaction is presented to show the application of our approach and to express the sensitivity analysis of parameters for building a fuzzy profile.

  10. Goguen categories a categorical approach to l-fuzzy relations

    CERN Document Server

    Winter, Michael; Mundici, Daniele

    2007-01-01

    Goguen categories extend the relational calculus and its categorical formalization to the fuzzy world. Starting from the fundamental concepts of sets, binary relations and lattices this book introduces several categorical formulations of an abstract theory of relations such as allegories, Dedekind categories and related structures. It is shown that neither theory is sufficiently rich to describe basic operations on fuzzy relations. The book then introduces Goguen categories and provides a comprehensive study of these structures including their representation theory, and the definability of norm-based operations. The power of the theory is demonstrated by a comprehensive example. A certain Goguen category is used to specify and to develop a fuzzy controller. Based on its abstract description as well as certain desirable properties and their formal proofs, a verified controller is derived without compromising the - sometimes - intuitive choice of norm-based operations by fuzzy engineers.

  11. Failure mode and effects analysis A fuzzy group MCDM approach

    Directory of Open Access Journals (Sweden)

    A. Hadi-Vencheh

    2013-08-01

    Full Text Available In this paper, a new fuzzy group decision making (FGDM model based on alpha-level sets, is proposed to generate, more accurate fuzzy using, risk priority numbers (RPNs and ensure to be robust against the uncertainty. This model allows decision makers (DMs to evaluate FMEA risk factors using linguistic terms rather than precise numerical values, allows them to express their opinions independently. A case study is investigated using the proposed model to illustrate its applications in RPN assessment.

  12. A Fuzzy-Logic Generalization of a Data Mining Approach

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin

    2001-01-01

    Roč. 11, č. 6 (2001), s. 595-610 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : data analysis * vague hypotheses * vague significante level * fuzzy prediacate calculus * basic fuzzy logic * generalized quantifiers * method GUHA Subject RIV: BA - General Mathematics

  13. Quadratic programming with fuzzy parameters: A membership function approach

    International Nuclear Information System (INIS)

    Liu, S.-T.

    2009-01-01

    Quadratic programming has been widely applied to solving real world problems. The conventional quadratic programming model requires the parameters to be known constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. This paper discusses the fuzzy quadratic programming problems where the cost coefficients, constraint coefficients, and right-hand sides are represented by convex fuzzy numbers. Since the parameters in the program are fuzzy numbers, the derived objective value is a fuzzy number as well. Using Zadeh's extension principle, a pair of two-level mathematical programs is formulated to calculate the upper bound and lower bound of the objective values of the fuzzy quadratic program. Based on the duality theorem and by applying the variable transformation technique, the pair of two-level mathematical programs is transformed into a family of conventional one-level quadratic programs. Solving the pair of quadratic programs produces the fuzzy objective values of the problem. An example illustrates method proposed in this paper.

  14. Automated mango fruit assessment using fuzzy logic approach

    Science.gov (United States)

    Hasan, Suzanawati Abu; Kin, Teoh Yeong; Sauddin@Sa'duddin, Suraiya; Aziz, Azlan Abdul; Othman, Mahmod; Mansor, Ab Razak; Parnabas, Vincent

    2014-06-01

    In term of value and volume of production, mango is the third most important fruit product next to pineapple and banana. Accurate size assessment of mango fruits during harvesting is vital to ensure that they are classified to the grade accordingly. However, the current practice in mango industry is grading the mango fruit manually using human graders. This method is inconsistent, inefficient and labor intensive. In this project, a new method of automated mango size and grade assessment is developed using RGB fiber optic sensor and fuzzy logic approach. The calculation of maximum, minimum and mean values based on RGB fiber optic sensor and the decision making development using minimum entropy formulation to analyse the data and make the classification for the mango fruit. This proposed method is capable to differentiate three different grades of mango fruit automatically with 77.78% of overall accuracy compared to human graders sorting. This method was found to be helpful for the application in the current agricultural industry.

  15. An integrated MCDM approach to green supplier selection

    Directory of Open Access Journals (Sweden)

    Morteza Yazdani

    2014-06-01

    Full Text Available Supplier selection management has been considered as an important subject for industrial organizations. In order to remain on the market, to gain profitability and to retain competitive advantage, business units need to establish an integrated and structured supplier selection system. In addition, environmental protection problems have been big solicitudes for organizations to consider green approach in supplier selection problem. However, finding proper suppliers involves several variables and it is critically a complex process. In this paper, the main attention is focused on finding the right supplier based on fuzzy multi criteria decision making (MCDM process. The weights of criteria are calculated by analytical hierarchical process (AHP and the final ranking is achieved by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS. TOPSIS advantage among the other similar methods is to obtain the best solution close to ideal solution. The paper attempts to express better understanding by an example of an automobile manufacturing supply chain.

  16. A new approach of active compliance control via fuzzy logic control for multifingered robot hand

    Science.gov (United States)

    Jamil, M. F. A.; Jalani, J.; Ahmad, A.

    2016-07-01

    Safety is a vital issue in Human-Robot Interaction (HRI). In order to guarantee safety in HRI, a model reference impedance control can be a very useful approach introducing a compliant control. In particular, this paper establishes a fuzzy logic compliance control (i.e. active compliance control) to reduce impact and forces during physical interaction between humans/objects and robots. Exploiting a virtual mass-spring-damper system allows us to determine a desired compliant level by understanding the behavior of the model reference impedance control. The performance of fuzzy logic compliant control is tested in simulation for a robotic hand known as the RED Hand. The results show that the fuzzy logic is a feasible control approach, particularly to control position and to provide compliant control. In addition, the fuzzy logic control allows us to simplify the controller design process (i.e. avoid complex computation) when dealing with nonlinearities and uncertainties.

  17. IMPROVEMENT OF THE F-PERCEPTORY APPROACH THROUGH MANAGEMENT OF FUZZY COMPLEX GEOGRAPHIC OBJECTS

    Directory of Open Access Journals (Sweden)

    B. Khalfi

    2015-08-01

    Full Text Available In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adaptation to fuzzy data. The F-Perceptory approachh manages the modeling of imperfect geographic information with UML. This management is essential to maintain faithfulness to reality and to better guide the user in his decision-making. However, this approach does not manage fuzzy complex geographic objects. The latter presents a multiple object with similar or different geographic shapes. So, in this paper, we propose to improve the F-Perceptory approach by proposing to handle fuzzy complex geographic objects modeling. In a second step, we propose its transformation to the UML modeling.

  18. Fuzzy interaction modelling for participants in innovation development: approaches and examples

    Directory of Open Access Journals (Sweden)

    CHERNOV Vladimir

    2018-01-01

    Full Text Available The article considers the interaction problems of the participants in innovative development at the regional level. Mathematical approaches and formulations for mode lling, such as the interaction on the basis of game approaches and the theory of fuzzy sets, have been proposed. In particular, the interaction model of innovative participants in the region, considered as a fuzzy coalition game, is presented. Its theoretical justification and an example of practical calculations are given. Further, the methodology of interaction modelling is considered , taking into account the motives of the participants in innovative development when forming fuzzy coalitions. An example of the corresponding calculations is also given. Also, the interaction model of "state-regions" in the interpretation of the fuzzy hierarchical game is proposed and described. The features of its solution are described and an example of calculations is presented.

  19. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    International Nuclear Information System (INIS)

    Ghyym, Seong Ho

    1998-01-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method

  20. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    Energy Technology Data Exchange (ETDEWEB)

    Ghyym, Seong Ho [KEPRI, Taejon (Korea, Republic of)

    1998-10-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method.

  1. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  2. An integrated multi attribute decision model for energy efficiency processes in petrochemical industry applying fuzzy set theory

    International Nuclear Information System (INIS)

    Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan

    2016-01-01

    Graphical abstract: Evaluation of compressors by comparing the different cost parameters. - Highlights: • Fuzzy sets and systems are used for decision making in MCDM problems. • An integrated Fuzzy AHP and fuzzy TOPSIS approaches are employed for compressor selection. • Compressor selection is a highly complex and non-linear process. • This approach increases the efficiency, reliability of alternative scenarios, and reduces the pay-back period. - Abstract: Energy efficient technologies offered by the market increases productivity. However, decision making for these technologies is usually obstructed in the firms and comes up with organizational barriers. Compressor selection in petrochemical industry requires assessment of several criteria such as ‘reliability, energy consumption, initial investment, capacity, pressure, and maintenance cost.’ Therefore, air compressor selection is a multi-attribute decision making (MADM) problem. The aim of this study is to select the most eligible compressor(s) so as to avoid the high energy consumption due to the capacity and maintenance costs. It is also aimed to avoid failures due to the reliability problems and high pressure. MADM usually takes place in a vague and imprecise environment. Soft computing techniques such as fuzzy sets and system can be used for decision making where vague and imprecise knowledge is available. In this study, an integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methodologies are employed for the compressor selection. Fuzzy AHP was used to determine the weights of criteria and fuzzy TOPSIS was employed to order the scenarios according to their superiority. The total effect of all criteria was determined for all alternative scenarios to make an optimal decision. Moreover, the types of compressor, carbon emission, waste heat recovery and their capacities were analyzed and compared by statistical

  3. A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

    Science.gov (United States)

    Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

    2013-01-01

    Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  4. A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

    Directory of Open Access Journals (Sweden)

    C. K. Kwong

    2013-01-01

    Full Text Available Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1 the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS failed to run due to a large number of inputs; (2 the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  5. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  6. A Geometric Fuzzy-Based Approach for Airport Clustering

    Directory of Open Access Journals (Sweden)

    Maria Nadia Postorino

    2014-01-01

    Full Text Available Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations.

  7. A fuzzy logic approach to modeling the underground economy in Taiwan

    Science.gov (United States)

    Yu, Tiffany Hui-Kuang; Wang, David Han-Min; Chen, Su-Jane

    2006-04-01

    The size of the ‘underground economy’ (UE) is valuable information in the formulation of macroeconomic and fiscal policy. This study applies fuzzy set theory and fuzzy logic to model Taiwan's UE over the period from 1960 to 2003. Two major factors affecting the size of the UE, the effective tax rate and the degree of government regulation, are used. The size of Taiwan's UE is scaled and compared with those of other models. Although our approach yields different estimates, similar patterns and leading are exhibited throughout the period. The advantage of applying fuzzy logic is twofold. First, it can avoid the complex calculations in conventional econometric models. Second, fuzzy rules with linguistic terms are easy for human to understand.

  8. Evaluation of service quality by using fuzzy MCDM: A case study in Iranian health-care centers

    Directory of Open Access Journals (Sweden)

    Leili Afkham

    2012-01-01

    Full Text Available Service quality plays an important role in health care systems since hospitals are responsible for people's lives. This study presents an effective approach for evaluating and comparing service qualities of four hospitals. Service quality consists of different attributes and many of them are intangible and difficult to measure. Therefore, we propose a fuzzy method to resolve the ambiguity of the concepts, which are associated with human judgments. SERVQUAL model is used to evaluate the respondents' judgments of service quality and multi attribute decision making approach is implemented for the comparison among hospitals. The paper use analytical hierarchy process (AHP for obtaining criteria weight and TOPSIS for ranking the cases.

  9. A Neuro-Fuzzy Approach in the Classification of Students’ Academic Performance

    Directory of Open Access Journals (Sweden)

    Quang Hung Do

    2013-01-01

    Full Text Available Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions.

  10. Fuzzy multinomial logistic regression analysis: A multi-objective programming approach

    Science.gov (United States)

    Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan

    2017-05-01

    Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.

  11. Application of integrated QFD and fuzzy AHP approach in selection of suppliers

    Directory of Open Access Journals (Sweden)

    Bojana Jovanović

    2014-10-01

    Full Text Available Supplier selection is a widely considered issue in the field of management, especially in quality management. In this paper, in the selection of suppliers of electronic components we used the integrated QFD and fuzzy AHP approaches. The QFD method is used as a tool for translating stakeholder needs into evaluating criteria for suppliers. The fuzzy AHP approach is used as a tool for prioritizing stakeholders, stakeholders’ requirements, evaluating criteria and, finally, for prioritizing suppliers. The paper showcases a case study of implementation of the integrated QFD and fuzzy AHP approaches in the selection of the electronic components supplier in one Serbian company that produces electronic devices. Also presented is the algorithm of implementation of the proposed approach. To the best of our knowledge, this is the first implementation of the proposed approach in a Serbian company.

  12. A Fast Approach to Bimatrix Games with Intuitionistic Fuzzy Payoffs

    Directory of Open Access Journals (Sweden)

    Min Fan

    2014-01-01

    Full Text Available The aim of this paper is to develop an effective method for solving bimatrix games with payoffs of intuitionistic fuzzy value. Firstly, bimatrix game model with intuitionistic fuzzy payoffs (IFPBiG was put forward. Secondly, two kinds of nonlinear programming algorithms were discussed with the Nash equilibrium of IFPBiG. Thirdly, Nash equilibrium of the algorithm was proved by the fixed point theory and the algorithm was simplified by linear programming methods. Finally, an example was solved through Matlab; it showed the validity, applicability, and superiority.

  13. Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2012-01-01

    Full Text Available This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean-variance (MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors' different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.

  14. Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

    Science.gov (United States)

    Lam, H K

    2012-02-01

    This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

  15. Fuzzy time series forecasting model with natural partitioning length approach for predicting the unemployment rate under different degree of confidence

    Science.gov (United States)

    Ramli, Nazirah; Mutalib, Siti Musleha Ab; Mohamad, Daud

    2017-08-01

    Fuzzy time series forecasting model has been proposed since 1993 to cater for data in linguistic values. Many improvement and modification have been made to the model such as enhancement on the length of interval and types of fuzzy logical relation. However, most of the improvement models represent the linguistic term in the form of discrete fuzzy sets. In this paper, fuzzy time series model with data in the form of trapezoidal fuzzy numbers and natural partitioning length approach is introduced for predicting the unemployment rate. Two types of fuzzy relations are used in this study which are first order and second order fuzzy relation. This proposed model can produce the forecasted values under different degree of confidence.

  16. Evaluation of purchase intention of customers in two wheeler automobile segment: AHP and TOPSIS

    Science.gov (United States)

    Sri Yogi, Kottala

    2018-03-01

    Winning heart of customers is preeminent main design of any business organization in global business environment. This paper explored customer’s priorities while purchasing a two wheeler automobile segment using Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a multi criteria decision making tools to accomplish the research objectives. Study has been done to analyze different criteria to be considered during purchasing of two wheeler automobiles among respondents using structured questionnaire based on SAATY scale. Based on our previous work on empirical & fuzzy logic approach to product quality and purchase intention of customers in two wheeler- operational, performance, economic, brand value and maintenance aspects are considered as decision criteria of customers while purchasing a two wheeler. The study suggests high pick up during overtaking, petrol saving, reasonable spare parts price, unique in design and identity and easy to change gear as main criterion in purchasing process. We also found some leading two wheeler automobiles models available in Indian market using some objective function criterion in choosing some important characteristics like price, cylinder capacity, brake horse power and weight during purchasing process of two wheeler automobile in Indian market based on respondents perception.

  17. Normal Forms for Fuzzy Logics: A Proof-Theoretic Approach

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2007-01-01

    Roč. 46, č. 5-6 (2007), s. 347-363 ISSN 1432-0665 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy logic * normal form * proof theory * hypersequents Subject RIV: BA - General Mathematics Impact factor: 0.620, year: 2007

  18. Fuzzy Approach in Ranking of Banks according to Financial Performances

    Directory of Open Access Journals (Sweden)

    Milena Jakšić

    2016-01-01

    Full Text Available Evaluating bank performance on a yearly basis and making comparison among banks in certain time intervals provide an insight into general financial state of banks and their relative position with respect to the environment (creditors, investors, and stakeholders. The aim of this study is to propose a new fuzzy multicriteria model to evaluate banks respecting relative importance of financial performances and their values. The relative importance of each pair of financial performance groups is assessed linguistic expressions which are modeled by triangular fuzzy numbers. Fuzzy Analytic Hierarchical Process (FAHP is applied to determine relative weights of the financial performances. In order to rank the treated banks, new model based on Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS is deployed. The proposed model is illustrated by an example giving real life data from 12 banks having 80% share of the Serbian market. In order to verify the proposed FTOPSIS different measures of separation are used. The presented solution enables the ranking of banks, gives an insight of bank’s state to stakeholders, and provides base for successful improvement in a field of strategy quality in bank business.

  19. Prioritising coastal zone management issues through fuzzy cognitive mapping approach.

    Science.gov (United States)

    Meliadou, Aleka; Santoro, Francesca; Nader, Manal R; Dagher, Manale Abou; Al Indary, Shadi; Salloum, Bachir Abi

    2012-04-30

    Effective public participation is an essential component of Integrated Coastal Zone Management implementation. To promote such participation, a shared understanding of stakeholders' objectives has to be built to ultimately result in common coastal management strategies. The application of quantitative and semi-quantitative methods involving tools such as Fuzzy Cognitive Mapping is presently proposed for reaching such understanding. In this paper we apply the Fuzzy Cognitive Mapping tool to elucidate the objectives and priorities of North Lebanon's coastal productive sectors, and to formalize their coastal zone perceptions and knowledge. Then, we investigate the potential of Fuzzy Cognitive Mapping as tool for support coastal zone management. Five round table discussions were organized; one for the municipalities of the area and one for each of the main coastal productive sectors (tourism, industry, fisheries, agriculture), where the participants drew cognitive maps depicting their views. The analysis of the cognitive maps showed a large number of factors perceived as affecting the current situation of the North Lebanon coastal zone that were classified into five major categories: governance, infrastructure, environment, intersectoral interactions and sectoral initiatives. Furthermore, common problems, expectations and management objectives for all sectors were exposed. Within this context, Fuzzy Cognitive Mapping proved to be an essential tool for revealing stakeholder knowledge and perception and understanding complex relationships. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    In this paper, we present a method to solve fully fuzzy linear systems with symmetric coefficient matrix. The symmetric coefficient matrix is decomposed into two systems of equations by using Cholesky method and then a solution can be obtained. Numerical examples are given to illustrate our method.

  1. Development of fuzzy air quality index using soft computing approach.

    Science.gov (United States)

    Mandal, T; Gorai, A K; Pathak, G

    2012-10-01

    Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.

  2. Maximum Power Point Tracking Control of Photovoltaic Systems: A Polynomial Fuzzy Model-Based Approach

    DEFF Research Database (Denmark)

    Rakhshan, Mohsen; Vafamand, Navid; Khooban, Mohammad Hassan

    2018-01-01

    This paper introduces a polynomial fuzzy model (PFM)-based maximum power point tracking (MPPT) control approach to increase the performance and efficiency of the solar photovoltaic (PV) electricity generation. The proposed method relies on a polynomial fuzzy modeling, a polynomial parallel......, a direct maximum power (DMP)-based control structure is considered for MPPT. Using the PFM representation, the DMP-based control structure is formulated in terms of SOS conditions. Unlike the conventional approaches, the proposed approach does not require exploring the maximum power operational point...

  3. Intuitionistic fuzzy-based model for failure detection.

    Science.gov (United States)

    Aikhuele, Daniel O; Turan, Faiz B M

    2016-01-01

    In identifying to-be-improved product component(s), the customer/user requirements which are mainly considered, and achieved through customer surveys using the quality function deployment (QFD) tool, often fail to guarantee or cover aspects of the product reliability. Even when they do, there are always many misunderstandings. To improve the product reliability and quality during product redesigning phase and to create that novel product(s) for the customers, the failure information of the existing product, and its component(s) should ordinarily be analyzed and converted to appropriate design knowledge for the design engineer. In this paper, a new intuitionistic fuzzy multi-criteria decision-making method has been proposed. The new approach which is based on an intuitionistic fuzzy TOPSIS model uses an exponential-related function for the computation of the separation measures from the intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) of alternatives. The proposed method has been applied to two practical case studies, and the result from the different cases has been compared with some similar computational approaches in the literature.

  4. A fuzzy-logic-based approach to qualitative safety modelling for marine systems

    International Nuclear Information System (INIS)

    Sii, H.S.; Ruxton, Tom; Wang Jin

    2001-01-01

    Safety assessment based on conventional tools (e.g. probability risk assessment (PRA)) may not be well suited for dealing with systems having a high level of uncertainty, particularly in the feasibility and concept design stages of a maritime or offshore system. By contrast, a safety model using fuzzy logic approach employing fuzzy IF-THEN rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. A fuzzy-logic-based approach may be more appropriately used to carry out risk analysis in the initial design stages. This provides a tool for working directly with the linguistic terms commonly used in carrying out safety assessment. This research focuses on the development and representation of linguistic variables to model risk levels subjectively. These variables are then quantified using fuzzy sets. In this paper, the development of a safety model using fuzzy logic approach for modelling various design variables for maritime and offshore safety based decision making in the concept design stage is presented. An example is used to illustrate the proposed approach

  5. Control Synthesis of Discrete-Time T-S Fuzzy Systems via a Multi-Instant Homogenous Polynomial Approach.

    Science.gov (United States)

    Xie, Xiangpeng; Yue, Dong; Zhang, Huaguang; Xue, Yusheng

    2016-03-01

    This paper deals with the problem of control synthesis of discrete-time Takagi-Sugeno fuzzy systems by employing a novel multiinstant homogenous polynomial approach. A new multiinstant fuzzy control scheme and a new class of fuzzy Lyapunov functions, which are homogenous polynomially parameter-dependent on both the current-time normalized fuzzy weighting functions and the past-time normalized fuzzy weighting functions, are proposed for implementing the object of relaxed control synthesis. Then, relaxed stabilization conditions are derived with less conservatism than existing ones. Furthermore, the relaxation quality of obtained stabilization conditions is further ameliorated by developing an efficient slack variable approach, which presents a multipolynomial dependence on the normalized fuzzy weighting functions at the current and past instants of time. Two simulation examples are given to demonstrate the effectiveness and benefits of the results developed in this paper.

  6. Fuzzy methods in decision making process - A particular approach in manufacturing systems

    Science.gov (United States)

    Coroiu, A. M.

    2015-11-01

    We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk

  7. Fuzzy logic approach for energetic and economic evaluation of hydroelectric projects

    International Nuclear Information System (INIS)

    Iliev, Atanas M.

    2003-01-01

    A mathematical model for energetic and economic evaluation of hydroelectric projects is developed. The main advantage of the proposed methodology is that the model considers uncertainty and vagueness which appears during the decision making process. Due to modeling of variables that are non statistical in their character, fuzzy logic approach is fully incorporated in the model. The first step in energetic evaluation of the hydro power projects is determination of the characteristic of the efficiency of the units to be installed in hydro power plants. For this purpose the model which uses the best characteristics of Artificial Network Fuzzy Inference System (ANFIS) is applied. The method is tested on real systems: HPP Tikves- the power plant in operation and HPP Kozjak - the power plant in construction. The results obtained from practical implementation show that the proposed approach gives superior results than classical polynomial approximation. The model for determining the consumption characteristic of hydro power plant is developed by Sugeno Fuzzy Logic System with polynomials in the consequent part of the rules. Model takes into account the variable gross head of HPP, as well as, the number of units which will be in operation for given output. Modeling of the gross head and power output are performed by expert's design membership functions. This model is practically applied on HPP Tikves for determination of the consumption characteristic for several gross head. The plausible yearly production of electricity from hydro power project, which is important for estimation of the benefit from the project, is calculated by mixed fuzzy-statistical model. hi this approach fuzzy set of the inflow is constructed according to the statistical parameters. The calculation of the production of electricity is realized for a several hydrological conditions which are described by linguistic variables. Finally, Mamdani Fuzzy Inference System with fuzzy number in consequent part

  8. A fuzzy logic approach to control anaerobic digestion.

    Science.gov (United States)

    Domnanovich, A M; Strik, D P; Zani, L; Pfeiffer, B; Karlovits, M; Braun, R; Holubar, P

    2003-01-01

    One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the next day, to obtain a high biogas quality and production. The biogas should contain a high methane concentration (over 50%) and a low concentration of components toxic for fuel cells, e.g. hydrogen sulphide, siloxanes, ammonia and mercaptanes. For producing data to test the control tool, four 20 l anaerobic Continuously Stirred Tank Reactors (CSTR) are operated. For controlling two systems were investigated: a pure fuzzy logic system and a hybrid-system which contains a fuzzy based reactor condition calculation and a hierachial neural net in a cascade of optimisation algorithms.

  9. Evaluation of Agile Suppliers Using Fuzzy MCDM Approach

    Directory of Open Access Journals (Sweden)

    Dursun Mehtap

    2016-01-01

    Full Text Available In today’s competitive environment, supply chain need to be of high speed and flexibility, i.e., agile. Agility has been proposed as a response to the high levels of complexity and uncertainty in modern markets. It is a business-wide capability that embraces organizational structures, information systems and logistics processes. This study employs the hierarchical fuzzy MCDM algorithm proposed by Karsak and Ahiska for the evaluation of agile suppliers. This algorithm is based on the proximity to the ideal solution concept and it can address the problems containing both crisp and fuzzy data. The application of the decision making method is illustrated through a case study conducted in a privet hospital and the results are analysed.

  10. Guaranteed cost control of polynomial fuzzy systems via a sum of squares approach.

    Science.gov (United States)

    Tanaka, Kazuo; Ohtake, Hiroshi; Wang, Hua O

    2009-04-01

    This paper presents the guaranteed cost control of polynomial fuzzy systems via a sum of squares (SOS) approach. First, we present a polynomial fuzzy model and controller that are more general representations of the well-known Takagi-Sugeno (T-S) fuzzy model and controller, respectively. Second, we derive a guaranteed cost control design condition based on polynomial Lyapunov functions. Hence, the design approach discussed in this paper is more general than the existing LMI approaches (to T-S fuzzy control system designs) based on quadratic Lyapunov functions. The design condition realizes a guaranteed cost control by minimizing the upper bound of a given performance function. In addition, the design condition in the proposed approach can be represented in terms of SOS and is numerically (partially symbolically) solved via the recent developed SOSTOOLS. To illustrate the validity of the design approach, two design examples are provided. The first example deals with a complicated nonlinear system. The second example presents micro helicopter control. Both the examples show that our approach provides more extensive design results for the existing LMI approach.

  11. A fuzzy quality function deployment approach to improve a component of a supervisory control and data acquisition system

    OpenAIRE

    Cristea Ciprian; Saşa Ciprian; Cristea Maria

    2017-01-01

    Monitoring and control of electric transformer stations, frequently spread out over small or large geographical areas, are achieved with supervisory control and data acquisition (SCADA). Quality function deployment (QFD) is a valuable analyzing tool in product design and development. To solve the uncertainty or inherent imprecision in QFD, many researchers have applied the fuzzy set theory to QFD and have developed various fuzzy QFD approaches. The literature regarding applying fuzzy QFD for ...

  12. Institutional Complexity and Social Entrepreneurship: A Fuzzy-Set Approach

    OpenAIRE

    Munoz, PA; Kibler, E

    2016-01-01

    This study examines the local institutional complexity of social entrepreneurship. Building on a novel fuzzy-set analysis of 407 social entrepreneurs in the UK, the study identifies five configurations of local institutional forces that collectively explain the confidence of social entrepreneurs in successfully managing their business. The findings demonstrate that local authorities are a dominant condition; yet combinations of other complementary—more and less formalized—local institutions n...

  13. Sensory Evaluation of the Selected Coffee Products Using Fuzzy Approach

    OpenAIRE

    M.A. Lazim; M. Suriani

    2009-01-01

    Knowing consumers' preferences and perceptions of the sensory evaluation of drink products are very significant to manufacturers and retailers alike. With no appropriate sensory analysis, there is a high risk of market disappointment. This paper aims to rank the selected coffee products and also to determine the best of quality attribute through sensory evaluation using fuzzy decision making model. Three products of coffee drinks were used for sensory evaluation. Data wer...

  14. A fuzzy hybrid approach for project manager selection

    Directory of Open Access Journals (Sweden)

    Ahmad Jafarnejad Chaghooshi

    2016-09-01

    Full Text Available Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA, all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.

  15. A Fuzzy Collaborative Forecasting Approach for Forecasting the Productivity of a Factory

    Directory of Open Access Journals (Sweden)

    Yi-Chi Wang

    2013-01-01

    Full Text Available Productivity is always considered as one of the most basic and important factors to the competitiveness of a factory. For this reason, all factories have sought to enhance productivity. To achieve this goal, we first need to estimate the productivity. However, there is considerable degree of uncertainty in productivity. For this reason, a fuzzy collaborative forecasting approach is proposed in this study to forecast the productivity of a factory. First, a learning model is established to estimate the future productivity. Subsequently, the learning model is converted into three equivalent nonlinear programming problems to be solved from various viewpoints. The fuzzy productivity forecasts by different experts may not be equal and should therefore be aggregated. To this end, the fuzzy intersection and back propagation network approach is applied. The practical example of a dynamic random access memory (DRAM factory is used to evaluate the effectiveness of the proposed methodology.

  16. A pertinent approach to solve nonlinear fuzzy integro-differential equations.

    Science.gov (United States)

    Narayanamoorthy, S; Sathiyapriya, S P

    2016-01-01

    Fuzzy integro-differential equations is one of the important parts of fuzzy analysis theory that holds theoretical as well as applicable values in analytical dynamics and so an appropriate computational algorithm to solve them is in essence. In this article, we use parametric forms of fuzzy numbers and suggest an applicable approach for solving nonlinear fuzzy integro-differential equations using homotopy perturbation method. A clear and detailed description of the proposed method is provided. Our main objective is to illustrate that the construction of appropriate convex homotopy in a proper way leads to highly accurate solutions with less computational work. The efficiency of the approximation technique is expressed via stability and convergence analysis so as to guarantee the efficiency and performance of the methodology. Numerical examples are demonstrated to verify the convergence and it reveals the validity of the presented numerical technique. Numerical results are tabulated and examined by comparing the obtained approximate solutions with the known exact solutions. Graphical representations of the exact and acquired approximate fuzzy solutions clarify the accuracy of the approach.

  17. A Fuzzy Approach of the Competition on the Air Transport Market

    Science.gov (United States)

    Charfeddine, Souhir; DeColigny, Marc; Camino, Felix Mora; Cosenza, Carlos Alberto Nunes

    2003-01-01

    The aim of this communication is to study with a new scope the conditions of the equilibrium in an air transport market where two competitive airlines are operating. Each airline is supposed to adopt a strategy maximizing its profit while its estimation of the demand has a fuzzy nature. This leads each company to optimize a program of its proposed services (frequency of the flights and ticket prices) characterized by some fuzzy parameters. The case of monopoly is being taken as a benchmark. Classical convex optimization can be used to solve this decision problem. This approach provides the airline with a new decision tool where uncertainty can be taken into account explicitly. The confrontation of the strategies of the companies, in the ease of duopoly, leads to the definition of a fuzzy equilibrium. This concept of fuzzy equilibrium is more general and can be applied to several other domains. The formulation of the optimization problem and the methodological consideration adopted for its resolution are presented in their general theoretical aspect. In the case of air transportation, where the conditions of management of operations are critical, this approach should offer to the manager elements needed to the consolidation of its decisions depending on the circumstances (ordinary, exceptional events,..) and to be prepared to face all possibilities. Keywords: air transportation, competition equilibrium, convex optimization , fuzzy modeling,

  18. A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

    Science.gov (United States)

    Osezua Aikhuele, Daniel; Mohd Turan, Faiz

    2016-02-01

    In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

  19. Fuzzy Linguistic Optimization on Multi-Attribute Machining

    Directory of Open Access Journals (Sweden)

    Tian-Syung Lan

    2010-06-01

    Full Text Available Most existing multi-attribute optimization researches for the modern CNC (computer numerical control turning industry were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff with three levels (low, medium, high are considered to optimize the multi-attribute (surface roughness, tool wear, and material removal rate finish turning. Through FAHP (Fuzzy Analytic Hierarchy Process with eighty intervals for each attribute, the weight of each attribute is evaluated from the paired comparison matrix constructed by the expert judgment. Additionally, twenty-seven fuzzy control rules using trapezoid membership function with respective to seventeen linguistic grades for each attribute are constructed. Considering thirty input and eighty output intervals, the defuzzifierion using center of gravity is thus completed. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution is moreover utilized to integrate and evaluate the multiple machining attributes for the Taguchi experiment, and thus the optimum general deduction parameters can then be received. The confirmation experiment for optimum general deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the attributes from the fuzzy linguistic optimization parameters are all significantly advanced comparing to those from benchmark. This paper not only proposes a general deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy linguistic approach for multiple CNC turning attributes with profound insight.

  20. Integration of fuzzy reasoning approach (FRA and fuzzy analytic hierarchy process (FAHP for risk assessment in mining industry

    Directory of Open Access Journals (Sweden)

    Shikha Verma

    2014-10-01

    Full Text Available Purpose: Mining industry has always been known for its unsafe working environment. This industry is one of the most hazard prone industries. To maintain safety in workplace timely assessment of risk associated with different operations performed to extract ore from the ore body has become necessity. To serve the said purpose, present work demonstrates a robust hybrid risk assessment approach for mining industry.Design/Methodology: Accident data from 1995 to 2012 is reviewed to identify hazards contributed to negative outcomes. The FRA approach is implemented to evaluate the risk levels associated with identified hazard factors. Thereafter AHP pairwise comparison matrix is developed to obtain priority weights for the hazard factors. Final priority of hazards based on severity of level of risk associated with them is obtained considering the outcome of FRA approach in terms of risk score for the hazards, combined with the priority weights obtained from AHP technique.Findings: Defuzzified FAHP weight of hazard factors, this weight gives priority sequence of hazards to be considered for development of plan of mitigation.Originality/Value: Risk assessment is a requirement of the Occupational Health and Safety Act 2000 (Section 7& 8. The data required to assess the risk is uncertain, and in such case fuzzy approach is well suited to process the data and get the crisp output. The output of fuzzy approach is made robust with its integration to AHP. In this way FAHP can be used as robust technique for risk assessment in this industry and this technique develops an efficient safety management system for the achievement of goal to develop the workplace with zero accident, which many other countries have already achieved.

  1. PERFORMANCE EVALUATION OF TURKISH TYPE A MUTUAL FUNDS AND PENSION STOCK FUNDS BY USING TOPSIS METHOD

    Directory of Open Access Journals (Sweden)

    Nesrin ALPTEKIN

    2009-07-01

    Full Text Available In this paper, it is evaluated performance of Turkish Type A mutual funds and pension stock funds by using TOPSIS method which is a multicriteria decision making approach. Both of these funds compose of stocks in their portfolios, so it can be enabled to compare each other. Generally, mutual or pension funds are evaluated according to their risk and return. At this point, it is used traditional performance measurement techniques of funds like Sharpe ratio, Sortino ratio, Treynor index and Jensen’s alpha. TOPSIS method takes into consideration all of these fund performance measurement techniques and provides more reasonable performance measurement.

  2. Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach

    Directory of Open Access Journals (Sweden)

    Ayad Hendalianpour

    2016-11-01

    Full Text Available Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with the objects in other clusters. The K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms are the most popular clustering algorithms for their easy implementation and fast work, but in some cases we cannot use these algorithms. Regarding this, in this paper, a hybrid model for customer clustering is presented that is applicable in five banks of Fars Province, Shiraz, Iran. In this way, the fuzzy relation among customers is defined by using their features described in linguistic and quantitative variables. As follows, the customers of banks are grouped according to K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms and the proposed Fuzzy Relation Clustering (FRC algorithm. The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables. Finally, we apply the proposed approach to five datasets of customer's segmentation in banks. The result of the FCR shows the accuracy and high performance of FRC compared other clustering methods.

  3. Estimation and Comparison of Underground Economy in Croatia and European Union Countries: Fuzzy Logic Approach

    Directory of Open Access Journals (Sweden)

    Kristina Marsic

    2016-06-01

    The purpose of this paper is to address this issue in three ways. First, we review existing estimates of the size of the underground economy. Second, we apply a novel calculation method for estimation: fuzzy logic. Third, we calculated and compared underground economy index for 25 European Union countries and compared it, with special focus on Croatian underground economy index. Results indicated that Croatia has the thirteenth largest underground economy among measured members of the European Union. This study is the first of its kind with recent data to measure the size of underground economy in European Union countries by employing fuzzy logic approach.

  4. Geometric Programming Approach to an Interactive Fuzzy Inventory Problem

    Directory of Open Access Journals (Sweden)

    Nirmal Kumar Mandal

    2011-01-01

    Full Text Available An interactive multiobjective fuzzy inventory problem with two resource constraints is presented in this paper. The cost parameters and index parameters, the storage space, the budgetary cost, and the objective and constraint goals are imprecise in nature. These parameters and objective goals are quantified by linear/nonlinear membership functions. A compromise solution is obtained by geometric programming method. If the decision maker is not satisfied with this result, he/she may try to update the current solution to his/her satisfactory solution. In this way we implement man-machine interactive procedure to solve the problem through geometric programming method.

  5. Optimization approach for saddling cost of medical cyclotrons with fuzziness

    International Nuclear Information System (INIS)

    Abass, S.A.; Massoud, E.M.A.

    2007-01-01

    Most radiation fields are combinations of different kinds of radiation. The radiations of most significance are fast neutrons, thermal neutrons, primary gammas and secondary gammas. Thermos's composite shielding materials are designed to attenuate these types of radiation. The shielding design requires an accurate cost-benefit analysis based on uncertainty optimization technique. The theory of fuzzy sets has been employed to formulate and solve the problem of cost-benefit analysis of medical cyclotron. This medical radioisotope production cyclotron is based in Sydney, Australia

  6. Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

    Directory of Open Access Journals (Sweden)

    Sohrab Kordrostami

    2016-07-01

    Full Text Available Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

  7. Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

    International Nuclear Information System (INIS)

    Balasubramaniam, P.; Kalpana, M.; Rakkiyappan, R.

    2012-01-01

    Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov—Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. (interdisciplinary physics and related areas of science and technology)

  8. Algorithms for finding Chomsky and Greibach normal forms for a fuzzy context-free grammar using an algebraic approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, E.T.

    1983-01-01

    Algorithms for the construction of the Chomsky and Greibach normal forms for a fuzzy context-free grammar using the algebraic approach are presented and illustrated by examples. The results obtained in this paper may have useful applications in fuzzy languages, pattern recognition, information storage and retrieval, artificial intelligence, database and pictorial information systems. 16 references.

  9. A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

    Science.gov (United States)

    Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi'i

    2017-11-01

    Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.

  10. Fuzzy Goal Programming Approach in Selective Maintenance Reliability Model

    Directory of Open Access Journals (Sweden)

    Neha Gupta

    2013-12-01

    Full Text Available 800x600 In the present paper, we have considered the allocation problem of repairable components for a parallel-series system as a multi-objective optimization problem and have discussed two different models. In first model the reliability of subsystems are considered as different objectives. In second model the cost and time spent on repairing the components are considered as two different objectives. These two models is formulated as multi-objective Nonlinear Programming Problem (MONLPP and a Fuzzy goal programming method is used to work out the compromise allocation in multi-objective selective maintenance reliability model in which we define the membership functions of each objective function and then transform membership functions into equivalent linear membership functions by first order Taylor series and finally by forming a fuzzy goal programming model obtain a desired compromise allocation of maintenance components. A numerical example is also worked out to illustrate the computational details of the method.  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4

  11. A fuzzy regression with support vector machine approach to the estimation of horizontal global solar radiation

    International Nuclear Information System (INIS)

    Baser, Furkan; Demirhan, Haydar

    2017-01-01

    Accurate estimation of the amount of horizontal global solar radiation for a particular field is an important input for decision processes in solar radiation investments. In this article, we focus on the estimation of yearly mean daily horizontal global solar radiation by using an approach that utilizes fuzzy regression functions with support vector machine (FRF-SVM). This approach is not seriously affected by outlier observations and does not suffer from the over-fitting problem. To demonstrate the utility of the FRF-SVM approach in the estimation of horizontal global solar radiation, we conduct an empirical study over a dataset collected in Turkey and applied the FRF-SVM approach with several kernel functions. Then, we compare the estimation accuracy of the FRF-SVM approach to an adaptive neuro-fuzzy system and a coplot supported-genetic programming approach. We observe that the FRF-SVM approach with a Gaussian kernel function is not affected by both outliers and over-fitting problem and gives the most accurate estimates of horizontal global solar radiation among the applied approaches. Consequently, the use of hybrid fuzzy functions and support vector machine approaches is found beneficial in long-term forecasting of horizontal global solar radiation over a region with complex climatic and terrestrial characteristics. - Highlights: • A fuzzy regression functions with support vector machines approach is proposed. • The approach is robust against outlier observations and over-fitting problem. • Estimation accuracy of the model is superior to several existent alternatives. • A new solar radiation estimation model is proposed for the region of Turkey. • The model is useful under complex terrestrial and climatic conditions.

  12. A fuzzy compromise programming approach for the Black-Litterman portfolio selection model

    Directory of Open Access Journals (Sweden)

    Mohsen Gharakhani

    2013-01-01

    Full Text Available In this paper, we examine advanced optimization approach for portfolio problem introduced by Black and Litterman to consider the shortcomings of Markowitz standard Mean-Variance optimization. Black and Litterman propose a new approach to estimate asset return. They present a way to incorporate the investor’s views into asset pricing process. Since the investor’s view about future asset return is always subjective and imprecise, we can represent it by using fuzzy numbers and the resulting model is multi-objective linear programming. Therefore, the proposed model is analyzed through fuzzy compromise programming approach using appropriate membership function. For this purpose, we introduce the fuzzy ideal solution concept based on investor preference and indifference relationships using canonical representation of proposed fuzzy numbers by means of their correspondingα-cuts. A real world numerical example is presented in which MSCI (Morgan Stanley Capital International Index is chosen as the target index. The results are reported for a portfolio consisting of the six national indices. The performance of the proposed models is compared using several financial criteria.

  13. An improved α-cut approach to transforming fuzzy membership function into basic belief assignment

    Directory of Open Access Journals (Sweden)

    Yang Yi

    2016-08-01

    Full Text Available In practical applications, pieces of evidence originated from different sources might be modeled by different uncertainty theories. To implement the evidence combination under the Dempster–Shafer evidence theory (DST framework, transformations from the other type of uncertainty representation into the basic belief assignment are needed. α-Cut is an important approach to transforming a fuzzy membership function into a basic belief assignment, which provides a bridge between the fuzzy set theory and the DST. Some drawbacks of the traditional α-cut approach caused by its normalization step are pointed out in this paper. An improved α-cut approach is proposed, which can counteract the drawbacks of the traditional α-cut approach and has good properties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved α-cut approach.

  14. Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

    Directory of Open Access Journals (Sweden)

    M.S. Osman

    2018-03-01

    Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

  15. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    International Nuclear Information System (INIS)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu

    2013-01-01

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management

  16. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu, E-mail: liyuxx8@hotmail.com

    2013-10-15

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management.

  17. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  18. Environmental impact assessment procedure: A new approach based on fuzzy logic

    International Nuclear Information System (INIS)

    Peche, Roberto; Rodriguez, Esther

    2009-01-01

    The information related to the different environmental impacts produced by the execution of activities and projects is often limited, described by semantic variables and, affected by a high degree of inaccuracy and uncertainty, thereby making fuzzy logic a suitable tool with which to express and treat this information. The present study proposes a new approach based on fuzzy logic to carry out the environmental impact assessment (EIA) of these activities and projects. Firstly, a set of impact properties is stated and two nondimensional parameters - ranging from 0 to 100 -are assigned, (p i ) to assess the value of the property and (v i ) to assess its contribution to each environmental impact. Next, the impact properties are described by means of fuzzy numbers p i - using generalised confidence intervals. Then, a procedure based on fuzzy arithmetic is developed to define the assessment functions v-bar = f(p-bar) - conventional mathematical functions, which incorporate the knowledge of these impact properties and give the fuzzy values v i - corresponding to each p i - . Subsequently, the fuzzy value of each environmental impact V-bar is estimated by aggregation of the values v i - , in order to obtain the total positive and negative environmental impacts V +- and V -- and, later - from them - the total environmental impact of the activity or project TV - . Finally, the defuzzyfication of TV - leads to a punctual impact estimator TV (1) - a conventional EI estimation - and its corresponding uncertainty interval estimator {(δ l (TV - ),δ r (TV - )}, which represent the total value of the environmental impact caused by the execution of the considered activity or project.

  19. A hybrid fuzzy MCDM approach to maintenance Quality Function Deployment

    Directory of Open Access Journals (Sweden)

    Davy George Valavi

    2015-01-01

    Full Text Available Maintenance Quality Function Deployment (MQFD is a model, which enhances the synergic power of Quality Function Deployment (QFD and Total Productive Maintenance (TPM. One of the crucial and important steps during the implementation of MQFD is the determination of the importance or weightages of the critical factors (CF and sub factors (SF. The CFs and SFs have to be compared precisely for the successful implementation of MQFD. The crisp pair-wise comparison in the conventional Analytical Hierarchy Process (AHP may be insufficient to determine the degree of weightage of CFs and SFs where vagueness and uncetainties are associated. In this paper, a modification of AHP based MQFD by incorporating fuzzy operations is proposed, which can improve the accuracy of determination of the weightages. A case study showing the applicability of this method is illustrated in this paper.

  20. A Fuzzy PROMETHEE Approach for Breast Cancer Treatment Techniques

    Directory of Open Access Journals (Sweden)

    Dilber Uzun Ozsahin

    2018-05-01

    Full Text Available Breast tumor is a growth that occur in the healthy breast tissue, whereby abnormal cells undergo division in an uncontrolled manner. It comes in different types and stages and the ability to metastasize and infect distant tissues. Several studies have showed that one in eight women in the US have develop breast cancer during their life time. Therefore, early diagnosis and treatment is widely approved as being essential to effectively alleviate the disease. The aim of this study is to comparatively analyze certain breast cancer treatment procedures which include surgery, hormone therapy, chemotherapy, and radiation therapy. Fuzzy PROMETHEE (preference ranking organization method for enrichment of evaluations a multi-criteria decision-making process was used to evaluate the treatments on factors that include side effects, overall survival rate, cost of treatment and treatment time.

  1. Social scientists in public health: a fuzzy approach

    Directory of Open Access Journals (Sweden)

    Juliana Luporini do Nascimento

    2015-05-01

    Full Text Available This study aims to describe and analyze the presence of social scientists, anthropologists, sociologists and political scientists in the field of public health. A survey by the Lattes Curriculum and sites of Medical Colleges, Institutes of Health Research Collective, seeking professionals who work in healthcare and have done some stage of their training in the areas of social sciences. In confluence with Norbert Elias' concepts of social networks and configuration of interdependence it was used fuzzy logic, and the tool free statistical software R version 2.12.0 which enabled a graphic representation of social scientists interdependence in the field of social sciences-health-social sciences. A total of 238 professionals were ready in 6 distinct clusters according to the distance or closer of each professional in relation to public health and social sciences. The work was shown with great analytical and graphical representation possibilities for social sciences of health, in using this innovative quantitative methodology.

  2. A Fuzzy Logic Approach to Marine Spatial Management

    Science.gov (United States)

    Teh, Lydia C. L.; Teh, Louise S. L.

    2011-04-01

    Marine spatial planning tends to prioritise biological conservation targets over socio-economic considerations, which may incur lower user compliance and ultimately compromise management success. We argue for more inclusion of human dimensions in spatial management, so that outcomes not only fulfill biodiversity and conservation objectives, but are also acceptable to resource users. We propose a fuzzy logic framework that will facilitate this task- The protected area suitability index (PASI) combines fishers' spatial preferences with biological criteria to assess site suitability for protection from fishing. We apply the PASI in a spatial evaluation of a small-scale reef fishery in Sabah, Malaysia. While our results pertain to fishers specifically, the PASI can also be customized to include the interests of other stakeholders and resource users, as well as incorporate varying levels of protection.

  3. Energy supply planning in Iran by using fuzzy linear programming approach (regarding uncertainties of investment costs)

    International Nuclear Information System (INIS)

    Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein

    2006-01-01

    For many years, energy models have been used in developed or developing countries to satisfy different needs in energy planning. One of major problems against energy planning and consequently energy models is uncertainty, spread in different economic, political and legal dimensions of energy planning. Confronting uncertainty, energy planners have often used two well-known strategies. The first strategy is stochastic programming, in which energy system planners define different scenarios and apply an explicit probability of occurrence to each scenario. The second strategy is Minimax Regret strategy that minimizes regrets of different decisions made in energy planning. Although these strategies have been used extensively, they could not flexibly and effectively deal with the uncertainties caused by fuzziness. 'Fuzzy Linear Programming (FLP)' is a strategy that can take fuzziness into account. This paper tries to demonstrate the method of application of FLP for optimization of supply energy system in Iran, as a case study. The used FLP model comprises fuzzy coefficients for investment costs. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be a serious competitor for other confronting uncertainties approaches, i.e. stochastic and Minimax Regret strategies. (author)

  4. A Literature Review Fuzzy Pay-Off-Method – A Modern Approach in Valuation

    Directory of Open Access Journals (Sweden)

    Daniel Manaţe

    2015-01-01

    Full Text Available This article proposes to present a modern approach in the analysis of updated cash flows. The approach is based on the Fuzzy Pay-Off-Method (FPOM for Real Option Valuation (ROV. This article describes a few types of models for the valuation of real options currently in use. In support for the chosen FPOM method, we included the mathematical model that stands at the basis of this method and a case study.

  5. Solving fully fuzzy transportation problem using pentagonal fuzzy numbers

    Science.gov (United States)

    Maheswari, P. Uma; Ganesan, K.

    2018-04-01

    In this paper, we propose a simple approach for the solution of fuzzy transportation problem under fuzzy environment in which the transportation costs, supplies at sources and demands at destinations are represented by pentagonal fuzzy numbers. The fuzzy transportation problem is solved without converting to its equivalent crisp form using a robust ranking technique and a new fuzzy arithmetic on pentagonal fuzzy numbers. To illustrate the proposed approach a numerical example is provided.

  6. A unified approach for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties

    Science.gov (United States)

    Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

    2017-09-01

    Automotive brake systems are always subjected to various types of uncertainties and two types of random-fuzzy uncertainties may exist in the brakes. In this paper, a unified approach is proposed for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties. In the proposed approach, two uncertainty analysis models with mixed variables are introduced to model the random-fuzzy uncertainties. The first one is the random and fuzzy model, in which random variables and fuzzy variables exist simultaneously and independently. The second one is the fuzzy random model, in which uncertain parameters are all treated as random variables while their distribution parameters are expressed as fuzzy numbers. Firstly, the fuzziness is discretized by using α-cut technique and the two uncertainty analysis models are simplified into random-interval models. Afterwards, by temporarily neglecting interval uncertainties, the random-interval models are degraded into random models, in which the expectations, variances, reliability indexes and reliability probabilities of system stability functions are calculated. And then, by reconsidering the interval uncertainties, the bounds of the expectations, variances, reliability indexes and reliability probabilities are computed based on Taylor series expansion. Finally, by recomposing the analysis results at each α-cut level, the fuzzy reliability indexes and probabilities can be obtained, by which the brake squeal instability can be evaluated. The proposed approach gives a general framework to deal with both types of random-fuzzy uncertainties that may exist in the brakes and its effectiveness is demonstrated by numerical examples. It will be a valuable supplement to the systematic study of brake squeal considering uncertainty.

  7. A Fuzzy Logic-Based Approach for Estimation of Dwelling Times of Panama Metro Stations

    Directory of Open Access Journals (Sweden)

    Aranzazu Berbey Alvarez

    2015-04-01

    Full Text Available Passenger flow modeling and station dwelling time estimation are significant elements for railway mass transit planning, but system operators usually have limited information to model the passenger flow. In this paper, an artificial-intelligence technique known as fuzzy logic is applied for the estimation of the elements of the origin-destination matrix and the dwelling time of stations in a railway transport system. The fuzzy inference engine used in the algorithm is based in the principle of maximum entropy. The approach considers passengers’ preferences to assign a level of congestion in each car of the train in function of the properties of the station platforms. This approach is implemented to estimate the passenger flow and dwelling times of the recently opened Line 1 of the Panama Metro. The dwelling times obtained from the simulation are compared to real measurements to validate the approach.

  8. A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

    Science.gov (United States)

    Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

    2018-04-01

    This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

  9. An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

    Directory of Open Access Journals (Sweden)

    Maryam Hourali

    2011-01-01

    Full Text Available In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut boundaries between concepts of the domains. To tackle this type of problems, one possible solution is to insert fuzzy logic into ontology construction process. In this article, a novel approach for fuzzy ontology generation with two uncertainty degrees is proposed. Hence, by implementing linguistic variables, uncertainty level in domain's concepts (Software Maintenance Engineering (SME domain has been modeled, and ontology relations have been modeled by fuzzy theory consequently. Then, we combined these uncertain models and proposed a new ontology with two degrees of uncertainty both in concept expression and relation expression. The generated fuzzy ontology was implemented for expansion of initial user's queries in SME domain. Experimental results showed that the proposed model has better overall retrieval performance comparing to keyword-based or crisp ontology-based retrieval systems.

  10. A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Sahoo, N.C. [Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka (Malaysia); Prasad, K. [Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka (Malaysia)

    2006-11-15

    This paper presents a fuzzy genetic approach for reconfiguration of radial distribution systems (RDS) so as to maximize the voltage stability of the network for a specific set of loads. The network reconfiguration involves a mechanism for selection of the best set of branches to be opened, one from each loop, such that the reconfigured RDS possesses desired performance characteristics. This discrete solution space is better handled by the proposed scheme, which maximizes a suitable optimizing function (computed using two different approaches). In the first approach, this function is chosen as the average of a voltage stability index of all the buses in the RDS, while in the second approach, the complete RDS is reduced to a two bus equivalent system and the optimizing function is the voltage stability index of this reduced two bus system. The fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution, and it also uses a fuzzy rule based mutation controller for efficient search of the solution space. This method, tested on 69 bus and 33 bus RDSs, shows promising results for the both approaches. It is also observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration. (author)

  11. A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems

    International Nuclear Information System (INIS)

    Sahoo, N.C.; Prasad, K.

    2006-01-01

    This paper presents a fuzzy genetic approach for reconfiguration of radial distribution systems (RDS) so as to maximize the voltage stability of the network for a specific set of loads. The network reconfiguration involves a mechanism for selection of the best set of branches to be opened, one from each loop, such that the reconfigured RDS possesses desired performance characteristics. This discrete solution space is better handled by the proposed scheme, which maximizes a suitable optimizing function (computed using two different approaches). In the first approach, this function is chosen as the average of a voltage stability index of all the buses in the RDS, while in the second approach, the complete RDS is reduced to a two bus equivalent system and the optimizing function is the voltage stability index of this reduced two bus system. The fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution, and it also uses a fuzzy rule based mutation controller for efficient search of the solution space. This method, tested on 69 bus and 33 bus RDSs, shows promising results for the both approaches. It is also observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration

  12. A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

    Directory of Open Access Journals (Sweden)

    Hossien Pourghassem

    2011-04-01

    Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

  13. A Fuzzy-MOORA approach for ERP system selection

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2012-07-01

    Full Text Available In today’s global and dynamic business environment, manufacturing organizations face the tremendous challenge of expanding markets and meeting the customer expectations. It compels them to lower total cost in the entire supply chain, shorten throughput time, reduce inventory, expand product choice, provide more reliable delivery dates and better customer service, improve quality, and efficiently coordinate demand, supply and production. In order to accomplish these objectives, the manufacturing organizations are turning to enterprise resource planning (ERP system, which is an enterprise-wide information system to interlace all the necessary business functions, such as product planning, purchasing, inventory control, sales, financial and human resources into a single system having a shared database. Thus to survive in the global competitive environment, implementation of a suitable ERP system is mandatory. However, selecting a wrong ERP system may adversely affect the manufacturing organization’s overall performance. Due to limitations in available resources, complexity of ERP systems and diversity of alternatives, it is often difficult for a manufacturing organization to select and install the most suitable ERP system. In this paper, two ERP system selection problems are solved using fuzzy multi-objective optimization on the basis of ratio analysis (MOORA method and it is observed that in both the cases, SAP is the best solution.

  14. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

    Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

    2017-03-01

    This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

  15. A multiresolutional approach to fuzzy text meaning: A first attempt

    Energy Technology Data Exchange (ETDEWEB)

    Mehler, A.

    1996-12-31

    The present paper focuses on the connotative meaning aspect of language signs especially above the level of words. In this context the view is taken that texts can be defined as a kind of supersign, to which-in the same way as to other signs-a meaning can be assigned. A text can therefore be described as the result of a sign articulation which connects the material text sign with a corresponding meaning. For the constitution of the structural text meaning a kind of a semiotic composition principle is responsible, which leads to the emergence of interlocked levels of language units, demonstrating different grades of resolution. Starting on the level of words, and going through the level of sentences this principle reaches finally the level of texts by aggregating step by step the meaning of a unit on a higher level out of the meanings of all components one level below, which occur within this unit. Besides, this article will elaborate the hypothesis that the meaning constitution as a two-stage process, corresponding to the syntagmatic and paradigmatic restrictions of language elements among each other, obtains equally on the level of texts. On text level this two-levelledness leads to the constitution of the connotative text meaning, whose constituents are determined on word level by the syntagmatic and paradigmatic relations of the words. The formalization of the text meaning representation occurs with the help of fuzzy set theory.

  16. University in a Region of Excellence: A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Janez Usenik

    2012-10-01

    Full Text Available The idea of establishing a university in the region southeast of Ljubljana has been festering for quite a few decades. The first attempts date back to the 1970s, but at that time the idea was still premature. The country in existence at that time did not allow for such discussions. After the assumption of independence of Slovenia, the hopes of having its own university in the southeast region reignited. Individuals and groups started with many activities and the possibility of establishing a university was becoming a reality. However, it should be noted that despite all efforts after twenty years there still is no university. Local and national authorities were changing and no one expressed anything against the establishment. Even local politicians included the establishment of a university in their program platforms; however till this date there still is no university. Will it finally happen?The article describes a model using fuzzy logic to determine the possibilities of establishing a university in relation to local and state interests.

  17. Expected value based fuzzy programming approach to solve integrated supplier selection and inventory control problem with fuzzy demand

    Science.gov (United States)

    Sutrisno; Widowati; Sunarsih; Kartono

    2018-01-01

    In this paper, a mathematical model in quadratic programming with fuzzy parameter is proposed to determine the optimal strategy for integrated inventory control and supplier selection problem with fuzzy demand. To solve the corresponding optimization problem, we use the expected value based fuzzy programming. Numerical examples are performed to evaluate the model. From the results, the optimal amount of each product that have to be purchased from each supplier for each time period and the optimal amount of each product that have to be stored in the inventory for each time period were determined with minimum total cost and the inventory level was sufficiently closed to the reference level.

  18. Fuzzy Group Decision Making Approach for Ranking Work Stations Based on Physical Pressure

    Directory of Open Access Journals (Sweden)

    Hamed Salmanzadeh

    2014-06-01

    Full Text Available This paper proposes a Fuzzy Group Decision Making approach for ranking work stations based on physical pressure. Fuzzy group decision making approach allows experts to evaluate different ergonomic factors using linguistic terms such as very high, high, medium, low, very low, rather than precise numerical values. In this way, there is no need to measure parameters and evaluation can be easily made in a group. According to ergonomics much work contents and situations, accompanied with multiple parameters and uncertainties, fuzzy group decision making is the best way to evaluate such a chameleon of concept. A case study was down to utilize the approach and illustrate its application in ergonomic assessment and ranking the work stations based on work pressure and found that this approach provides flexibility, practicality, efficiency in making decision around ergonomics areas. The normalized defuzzification numbers which are resulted from this method are compared with result of quantitative assessment of Automotive Assembly Work Sheet auto, it’s demonstrated that the proposed method result is 10% less than Automotive Assembly Work Sheet, approximately.

  19. Application of grey-fuzzy approach in parametric optimization of EDM process in machining of MDN 300 steel

    Science.gov (United States)

    Protim Das, Partha; Gupta, P.; Das, S.; Pradhan, B. B.; Chakraborty, S.

    2018-01-01

    Maraging steel (MDN 300) find its application in many industries as it exhibits high hardness which are very difficult to machine material. Electro discharge machining (EDM) is an extensively popular machining process which can be used in machining of such materials. Optimization of response parameters are essential for effective machining of these materials. Past researchers have already used Taguchi for obtaining the optimal responses of EDM process for this material with responses such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) considering discharge current, pulse on time, pulse off time, arc gap, and duty cycle as process parameters. In this paper, grey relation analysis (GRA) with fuzzy logic is applied to this multi objective optimization problem to check the responses by an implementation of the derived parametric setting. It was found that the parametric setting derived by the proposed method results in better a response than those reported by the past researchers. Obtained results are also verified using the technique for order of preference by similarity to ideal solution (TOPSIS). The predicted result also shows that there is a significant improvement in comparison to the results of past researchers.

  20. Performance evaluation and ranking of direct sales stores using BSC approach and fuzzy multiple attribute decision-making methods

    Directory of Open Access Journals (Sweden)

    Mojtaba Soltannezhad Dizaji

    2017-07-01

    Full Text Available In an environment where markets go through a volatile process, and rapid fundamental changes occur due to technological advances, it is important to ensure and maintain a good performance measurement. Organizations, in their performance evaluation, should consider different types of financial and non-financial indicators. In systems like direct sales stores in which decision units have multiple inputs and outputs, all criteria influencing on performance must be combined and examined in a system, simultaneously. The purpose of this study is to evaluate the performance of different products through direct sales of a firm named Shirin Asal with a combination of Balanced Scorecard, fuzzy AHP and TOPSIS so that the weaknesses of subjectivity and selective consideration of evaluators in evaluating the performance indicators are reduced and evaluation integration is provided by considering the contribution of each indicator and each indicator group of balanced scorecard. The research method of this case study is applied. The data collection method is a questionnaire from the previous studies, the use of experts' opinions and the study of documents in the organization. MATLAB and SPSS were used to analyze the data. During this study, the customer and financial perspectives are of the utmost importance to assess the company branches. Among the sub-criteria, the rate of new customer acquisition in the customer dimension and the net income to sales ratio in financial dimension are of the utmost importance.

  1. Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

    Directory of Open Access Journals (Sweden)

    Amin Zadeh Sarraf

    2013-09-01

    Full Text Available Purpose: Numerous companies are expecting their knowledge management (KM to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. Design/methodology/approach: An extension of TOPSIS, a multi-attribute decision making (MADM technique, to a group decision environment is investigated. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. The entropy method is often used for assessing weights in the TOPSIS method. Entropy in information theory is a criterion uses for measuring the amount of disorder represented by a discrete probability distribution. According to decrease resistance degree of employees opposite of implementing a new strategy, it seems necessary to spot all managers’ opinion. The normal distribution considered the most prominent probability distribution in statistics is used to normalize gathered data. Findings: The results of this study show that by considering 6 criteria for alternatives Evaluation, the most appropriate KM strategy to implement  in our company was ‘‘Personalization’’. Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the approach such as normal distribution of sample and community. These assumptions can be changed in future work. Originality/value: This paper proposes an effective solution based on combined entropy and TOPSIS approach to help companies that need to evaluate and select KM strategies. In represented solution, opinions of all managers is gathered and normalized by using standard normal distribution and central limit theorem. Keywords: Knowledge management; strategy; TOPSIS; Normal distribution; entropy

  2. NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

    Energy Technology Data Exchange (ETDEWEB)

    Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

    2016-02-15

    The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

  3. NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

    International Nuclear Information System (INIS)

    Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

    2016-01-01

    The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

  4. A Fuzzy Approach Using Generalized Dinkelbach’s Algorithm for Multiobjective Linear Fractional Transportation Problem

    Directory of Open Access Journals (Sweden)

    Nurdan Cetin

    2014-01-01

    Full Text Available We consider a multiobjective linear fractional transportation problem (MLFTP with several fractional criteria, such as, the maximization of the transport profitability like profit/cost or profit/time, and its two properties are source and destination. Our aim is to introduce MLFTP which has not been studied in literature before and to provide a fuzzy approach which obtain a compromise Pareto-optimal solution for this problem. To do this, first, we present a theorem which shows that MLFTP is always solvable. And then, reducing MLFTP to the Zimmermann’s “min” operator model which is the max-min problem, we construct Generalized Dinkelbach’s Algorithm for solving the obtained problem. Furthermore, we provide an illustrative numerical example to explain this fuzzy approach.

  5. Systematic design approach of fuzzy PID stabilizer for DC-DC converters

    International Nuclear Information System (INIS)

    Guesmi, K.; Essounbouli, N.; Hamzaoui, A.

    2008-01-01

    DC-DC converters process electrical energy by switching between a fixed number of configurations. The objective of controlling these systems is to provide better performances, ensure closed loop stability and guarantee a simple predictable behaviour. Based on a converter averaged model, we propose, in this paper, a systematic design approach of a fuzzy PID. The choice of controller parameters stands on the whole system stability requirements. Extension of the obtained asymptotic stability to structural stability is presented to show that the developed controller ensures also a simple and predictable behaviour of the converter. Finally, we illustrate the efficiency of the proposed fuzzy PID design approach through simulations in voltage mode as well as in current mode control

  6. Motion control of planar parallel robot using the fuzzy descriptor system approach.

    Science.gov (United States)

    Vermeiren, Laurent; Dequidt, Antoine; Afroun, Mohamed; Guerra, Thierry-Marie

    2012-09-01

    This work presents the control of a two-degree of freedom parallel robot manipulator. A quasi-LPV approach, through the so-called TS fuzzy model and LMI constraints problems is used. Moreover, in this context a way to derive interesting control laws is to keep the descriptor form of the mechanical system. Therefore, new LMI problems have to be defined that helps to reduce the conservatism of the usual results. Some relaxations are also proposed to leave the pure quadratic stability/stabilization framework. A comparison study between the classical control strategies from robotics and the control design using TS fuzzy descriptor models is carried out to show the interest of the proposed approach. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Mathematical solution of multilevel fractional programming problem with fuzzy goal programming approach

    Science.gov (United States)

    Lachhwani, Kailash; Poonia, Mahaveer Prasad

    2012-08-01

    In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.

  8. Systematic design approach of fuzzy PID stabilizer for DC-DC converters

    Energy Technology Data Exchange (ETDEWEB)

    Guesmi, K.; Essounbouli, N.; Hamzaoui, A. [CReSTIC, IUT de Troyes 09, rue de Quebec BP. 396, 10026 Troyes (France)

    2008-10-15

    DC-DC converters process electrical energy by switching between a fixed number of configurations. The objective of controlling these systems is to provide better performances, ensure closed loop stability and guarantee a simple predictable behaviour. Based on a converter averaged model, we propose, in this paper, a systematic design approach of a fuzzy PID. The choice of controller parameters stands on the whole system stability requirements. Extension of the obtained asymptotic stability to structural stability is presented to show that the developed controller ensures also a simple and predictable behaviour of the converter. Finally, we illustrate the efficiency of the proposed fuzzy PID design approach through simulations in voltage mode as well as in current mode control. (author)

  9. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach

    International Nuclear Information System (INIS)

    Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.

    2008-01-01

    This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm

  10. Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

    Science.gov (United States)

    Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

    2014-09-01

    Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

  11. A Fuzzy Decision Making Approach for Supplier Selection in Healthcare Industry

    OpenAIRE

    Zeynep Sener; Mehtap Dursun

    2014-01-01

    Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision meth...

  12. Health-Care Waste Treatment Technology Selection Using the Interval 2-Tuple Induced TOPSIS Method

    Directory of Open Access Journals (Sweden)

    Chao Lu

    2016-06-01

    Full Text Available Health-care waste (HCW management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi-granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete. Therefore, the main objective of this study is to propose a new hybrid decision making approach combining interval 2-tuple induced distance operators with the technique for order preference by similarity to an ideal solution (TOPSIS for tackling HCW treatment technology selection problems with linguistic information. The proposed interval 2-tuple induced TOPSIS (ITI-TOPSIS can not only model the uncertainty and diversity of the assessment information given by decision makers, but also reflect the complex attitudinal characters of decision makers and provide much more complete information for the selection of the optimum disposal alternative. Finally, an empirical example in Shanghai, China is provided to illustrate the proposed decision making method, and results show that the ITI-TOPSIS proposed in this paper can solve the problem of HCW treatment technology selection effectively.

  13. Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

    Directory of Open Access Journals (Sweden)

    Yuanjiang Huang

    2014-01-01

    Full Text Available The sensor nodes in the Wireless Sensor Networks (WSNs are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC, of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC, of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.

  14. A fuzzy-based particle swarm optimisation approach for task assignment in home healthcare

    Directory of Open Access Journals (Sweden)

    Mutingi, Michael

    2014-11-01

    Full Text Available Home healthcare (HHC organisations provide coordinated healthcare services to patients at their homes. Motivated by the ever-increasing need for home-based care, the assignment of tasks to available healthcare staff is a common and complex problem in homecare organisations. Designing high quality task schedules is critical for improving worker morale, job satisfaction, service efficiency, service quality, and competitiveness over the long term. The desire is to provide high quality task assignment schedules that satisfy the patient, the care worker, and the management. This translates to maximising schedule fairness in terms of workload assignments, avoiding task time window violation, and meeting management goals as much as possible. However, in practice, these desires are often subjective as they involve imprecise human perceptions. This paper develops a fuzzy multi-criteria particle swarm optimisation (FPSO approach for task assignment in a home healthcare setting in a fuzzy environment. The proposed approach uses a fuzzy evaluation method from a multi-criteria point of view. Results from illustrative computational experiments show that the approach is promising.

  15. Short-term load forecasting by a neuro-fuzzy based approach

    Energy Technology Data Exchange (ETDEWEB)

    Ruey-Hsun Liang; Ching-Chi Cheng [National Yunlin University of Science and Technology (China). Dept. of Electrical Engineering

    2002-02-01

    An approach based on an artificial neural network (ANN) combined with a fuzzy system is proposed for short-term load forecasting. This approach was developed in order to reach the desired short-term load forecasting in an efficient manner. Over the past few years, ANNs have attained the ability to manage a great deal of system complexity and are now being proposed as powerful computational tools. In order to select the appropriate load as the input for the desired forecasting, the Pearson analysis method is first applied to choose two historical record load patterns that are similar to the forecasted load pattern. These two load patterns and the required weather parameters are then fuzzified and input into a neural network for training or testing the network. The back-propagation (BP) neural network is applied to determine the preliminary forecasted load. In addition, the rule base for the fuzzy inference machine contains important linguistic membership function terms with knowledge in the form of fuzzy IF-THEN rules. This produces the load correction inference from the historical information and past forecasted load errors to obtain an inferred load error. Adding the inferred load error to the preliminary forecasted load, we can obtain the finial forecasted load. The effectiveness of the proposed approach to the short-term load-forecasting problem is demonstrated using practical data from the Taiwan Power Company (TPC). (Author)

  16. The effects of exchange rate volatility on international trade fl ows: evidence from panel data analysis and fuzzy approach

    Directory of Open Access Journals (Sweden)

    Robert M. Kunst

    2012-06-01

    Full Text Available The aim of this paper is to analyze the effects of exchange rate volatility on international trade flows by using two different approaches, the panel data analysis and fuzzy logic, and to compare the results. To a panel with the crosssection dimension of 91 pairs of EU15 countries and with time ranging from 1964 to 2003, an extended gravity model of trade is applied in order to determine theeffects of exchange rate volatility on bilateral trade flows of EU15 countries. The estimated impact is clearly negative, which indicates that exchange rate volatility has a negative influence on bilateral trade flows. Then, this traditional panel approach is contrasted with an alternative investigation based on fuzzy logic. The key elements of the fuzzy approach are to set fuzzy decision rules and to assignmembership functions to the fuzzy sets intuitively based on experience. Both approaches yield very similar results and fuzzy approach is recommended to be used as a complement to statistical methods.

  17. Introduction to Fuzzy Set Theory

    Science.gov (United States)

    Kosko, Bart

    1990-01-01

    An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

  18. Rabies epidemic model with uncertainty in parameters: crisp and fuzzy approaches

    Science.gov (United States)

    Ndii, M. Z.; Amarti, Z.; Wiraningsih, E. D.; Supriatna, A. K.

    2018-03-01

    A deterministic mathematical model is formulated to investigate the transmission dynamics of rabies. In particular, we investigate the effects of vaccination, carrying capacity and the transmission rate on the rabies epidemics and allow for uncertainty in the parameters. We perform crisp and fuzzy approaches. We find that, in the case of crisp parameters, rabies epidemics may be interrupted when the carrying capacity and the transmission rate are not high. Our findings suggest that limiting the growth of dog population and reducing the potential contact between susceptible and infectious dogs may aid in interrupting rabies epidemics. We extend the work by considering a fuzzy carrying capacity and allow for low, medium, and high level of carrying capacity. The result confirms the results obtained by using crisp carrying capacity, that is, when the carrying capacity is not too high, the vaccination could confine the disease effectively.

  19. Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach

    Science.gov (United States)

    Chowdhury, R.; Adhikari, S.

    2012-10-01

    Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.

  20. Fuzzy logic approach to SWOT analysis for economics tasks and example of its computer realization

    Directory of Open Access Journals (Sweden)

    Vladimir CHERNOV

    2016-07-01

    Full Text Available The article discusses the widely used classic method of analysis, forecasting and decision-making in the various economic problems, called SWOT analysis. As known, it is a qualitative comparison of multicriteria degree of Strength, Weakness, Opportunity, Threat for different kinds of risks, forecasting the development in the markets, status and prospects of development of enterprises, regions and economic sectors, territorials etc. It can also be successfully applied to the evaluation and analysis of different project management tasks - investment, innovation, marketing, development, design and bring products to market and so on. However, in practical competitive market and economic conditions, there are various uncertainties, ambiguities, vagueness. Its making usage of SWOT analysis in the classical sense not enough reasonable and ineffective. In this case, the authors propose to use fuzzy logic approach and the theory of fuzzy sets for a more adequate representation and posttreatment assessments in the SWOT analysis. In particular, has been short showed the mathematical formulation of respective task and the main approaches to its solution. Also are given examples of suitable computer calculations in specialized software Fuzicalc for processing and operations with fuzzy input data. Finally, are presented considerations for interpretation of the results.

  1. New approach to solve fully fuzzy system of linear equations using ...

    Indian Academy of Sciences (India)

    This paper proposes two new methods to solve fully fuzzy system of linear equations. The fuzzy system has been converted to a crisp system of linear equations by using single and double parametric form of fuzzy numbers to obtain the non-negative solution. Double parametric form of fuzzy numbers is defined and applied ...

  2. A COMBINED FUZZY MCDM APPROACH FOR IDENTIFYING THE SUITABLE LANDS FOR URBAN DEVELOPMENT: AN EXAMPLE FROM BANDAR ABBS, IRAN

    Directory of Open Access Journals (Sweden)

    Mohsen Dadras

    2014-01-01

    Full Text Available This study aims at identifying the suitable lands for urban dev elopment in Bandar Abbas city based on its real world use regarding specific crite ria and sub-criteria. The city of Bandar Abbas is considered as the most important commer cial and economic city of Iran. It is also considered as one of the major cities of Iran which has played a pivotal role in the country's development and progress in recen t years especially after the end of Iran-Iraq war owing to its embracing the country's m ain commercial ports. This process has caused the immigration rate into the city to rise significantly over the past 20 years. Thus, the development of the city is meanwhile c onsidered as a high priority. Bandar Abbas city does not have a rich capacity for g rowth and development due to its special geographical situation being located in coastal border. Among the limitations placed in the city's development way, natural limit ations (heights and sea shore in the northern and southern parts of the city and struc tural limitations (military centers in the east and west sides of the city may be referred . Therefore, identifying the suitable lands for urban development within Bandar Abbas city l imits is becoming an essential priority. Therefore, d ifferent quantitative and quali tative criteria have been studied in order to select and identify these lands. The struct ures of qualitative criteria for most parts involve ambiguities and vagueness. This leads us to use Fuzzy logic in this study as a natural method for determining the solutions fo r problems of Multi- criteria decision making (MCDM. In the current research, a com bination of MCDM methods has been presented for analysis. To assignee weights of the criteria Fuzzy AHP (analytic hierarchy process is used for land selection and Fuzzy TOPSIS (method for order priority by similarity to ideal solution is utilized to choose the alternative that is the most appropriate through these criteria weights. The

  3. A neural-fuzzy approach to classify the ecological status in surface waters

    International Nuclear Information System (INIS)

    Ocampo-Duque, William; Schuhmacher, Marta; Domingo, Jose L.

    2007-01-01

    A methodology based on a hybrid approach that combines fuzzy inference systems and artificial neural networks has been used to classify ecological status in surface waters. This methodology has been proposed to deal efficiently with the non-linearity and highly subjective nature of variables involved in this serious problem. Ecological status has been assessed with biological, hydro-morphological, and physicochemical indicators. A data set collected from 378 sampling sites in the Ebro river basin has been used to train and validate the hybrid model. Up to 97.6% of sampling sites have been correctly classified with neural-fuzzy models. Such performance resulted very competitive when compared with other classification algorithms. With non-parametric classification-regression trees and probabilistic neural networks, the predictive capacities were 90.7% and 97.0%, respectively. The proposed methodology can support decision-makers in evaluation and classification of ecological status, as required by the EU Water Framework Directive. - Fuzzy inference systems can be used as environmental classifiers

  4. Profitability analysis of a femtosecond laser system for cataract surgery using a fuzzy logic approach.

    Science.gov (United States)

    Trigueros, José Antonio; Piñero, David P; Ismail, Mahmoud M

    2016-01-01

    To define the financial and management conditions required to introduce a femtosecond laser system for cataract surgery in a clinic using a fuzzy logic approach. In the simulation performed in the current study, the costs associated to the acquisition and use of a commercially available femtosecond laser platform for cataract surgery (VICTUS, TECHNOLAS Perfect Vision GmbH, Bausch & Lomb, Munich, Germany) during a period of 5y were considered. A sensitivity analysis was performed considering such costs and the countable amortization of the system during this 5y period. Furthermore, a fuzzy logic analysis was used to obtain an estimation of the money income associated to each femtosecond laser-assisted cataract surgery (G). According to the sensitivity analysis, the femtosecond laser system under evaluation can be profitable if 1400 cataract surgeries are performed per year and if each surgery can be invoiced more than $500. In contrast, the fuzzy logic analysis confirmed that the patient had to pay more per surgery, between $661.8 and $667.4 per surgery, without considering the cost of the intraocular lens (IOL). A profitability of femtosecond laser systems for cataract surgery can be obtained after a detailed financial analysis, especially in those centers with large volumes of patients. The cost of the surgery for patients should be adapted to the real flow of patients with the ability of paying a reasonable range of cost.

  5. Using neuro-fuzzy based approach for the evaluation of turbine-generator outputs

    International Nuclear Information System (INIS)

    Chan, Y. K.; Lu, C. C.; Chang, C. J.; Kao, L.; Hong, L. C.

    2010-01-01

    The objective of this study is to develop a hybrid soft-computing modeling technique used to develop the steam turbine cycle model for Chinshan Nuclear Power Station (CNPS). The technique uses neuro-fuzzy model to predict the turbine-generator output. Firstly, the station past three fuel cycles operating data above 95% load were collected and validated as the baseline performance data set. Then, the signal errors for new operating data were detected by comparison with the baseline data set and their allowable range of variations. Finally, the most important parameters were selected as an input of the neuro-fuzzy based steam turbine cycle model. After training and testing with key parameters including throttle pressure, condenser back pressure, feedwater mass flow, and final feedwater temperature, the proposed model can be applied to predict the turbine-generator output. The analysis results show this neuro-fuzzy based turbine cycle model can be used to predict the generator output with a good agreement. Moreover, the achievement of this study provides an alternative approach in thermal performance evaluation for nuclear power stations. (authors)

  6. An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

    Science.gov (United States)

    Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

    2016-01-01

    This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

  7. Real-time process signal validation based on neuro-fuzzy and possibilistic approach

    International Nuclear Information System (INIS)

    Figedy, S.; Fantoni, P.F.; Hoffmann, M.

    2001-01-01

    Real-time process signal validation is an application field where the use of fuzzy logic and Artificial Neural Networks can improve the diagnostics of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process is to be performed. The possibilistic approach allows a fast detection of unforeseen plant conditions. Specialized Artificial Neural Networks are used, one for each fuzzy cluster. This offers two main advantages: the accuracy and generalization capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This system analyzes the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. This model has been tested on a simulated data from the PWR type of a nuclear power plant, to monitor safety-related reactor variables over the entire power-flow operating map and were installed in real conditions of BWR nuclear reactor. (Authors)

  8. A multi-objective fuzzy mathematical approach for sustainable reverse supply chain configuration

    Directory of Open Access Journals (Sweden)

    Jyoti D. Darbari

    2017-03-01

    Full Text Available Background: Designing and implementation of reverse logistics (RL network which meets the sustainability targets have been a matter of emerging concern for the electronics companies in India. Objectives: The present study developed a two-phase model for configuration of sustainable RL network design for an Indian manufacturing company to manage its end-of-life and endof-use electronic products. The notable feature of the model was the evaluation of facilities under financial, environmental and social considerations and integration of the facility selection decisions with the network design. Method: In the first phase, an integrated Analytical Hierarchical Process Complex Proportional Assessment methodology was used for the evaluation of the alternative locations in terms of their degree of utility, which in turn was based on the three dimensions of sustainability. In the second phase, the RL network was configured as a bi-objective programming problem, and fuzzy optimisation approach was utilised for obtaining a properly efficient solution to the problem. Results: The compromised solution attained by the proposed fuzzy model demonstrated that the cost differential for choosing recovery facilities with better environmental and social performance was not significant; therefore, Indian manufacturers must not compromise on the sustainability aspects for facility location decisions. Conclusion: The results reaffirmed that the bi-objective fuzzy decision-making model can serve as a decision tool for the Indian manufacturers in designing a sustainable RL network. The multi-objective optimisation model captured a reasonable trade-off between the fuzzy goals of minimising the cost of the RL network and maximising the sustainable performance of the facilities chosen.

  9. A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

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    Vahid Reza Salamat

    2018-09-01

    Full Text Available The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1 Resource-based view, and (2 Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a novel development of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed.

  10. The External Performance Appraisal of China Energy Regulation: An Empirical Study Using a TOPSIS Method Based on Entropy Weight and Mahalanobis Distance.

    Science.gov (United States)

    Wang, Zheng-Xin; Li, Dan-Dan; Zheng, Hong-Hao

    2018-01-30

    In China's industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved technique for order preference by similarity to an ideal solution based on entropy weight and Mahalanobis distance (briefly referred as E-M-TOPSIS). The performance of the approach was verified to be satisfactory. By separately using traditional and improved TOPSIS methods, the study carried out the empirical appraisals on the external performance of China's energy regulation during 1999~2015. The results show that the correlation between the performance indexes causes the significant difference between the appraisal results of E-M-TOPSIS and traditional TOPSIS. The E-M-TOPSIS takes the correlation between indexes into account and generally softens the closeness degree compared with traditional TOPSIS. Moreover, it makes the relative closeness degree fluctuate within a small-amplitude. The results conform to the practical condition of China's energy regulation and therefore the E-M-TOPSIS is favorably applicable for the external performance appraisal of energy regulation. Additionally, the external economic performance and social responsibility performance (including environmental and energy safety performances) based on the E-M-TOPSIS exhibit significantly different fluctuation trends. The external economic performance dramatically fluctuates with a larger fluctuation amplitude, while the social responsibility performance exhibits a relatively stable interval fluctuation. This indicates that compared to the social responsibility performance, the fluctuation of external economic performance is more sensitive to energy regulation.

  11. FGP Approach for Solving Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy parameters

    Directory of Open Access Journals (Sweden)

    m. s. osman

    2017-09-01

    Full Text Available In this paper, we consider fuzzy goal programming (FGP approach for solving multi-level multi-objective quadratic fractional programming (ML-MOQFP problem with fuzzy parameters in the constraints. Firstly, the concept of the ?-cut approach is applied to transform the set of fuzzy constraints into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into quadratic objective functions based on a proposed transformation. Secondly, the FGP approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach.

  12. Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm–based adaptive neuro-fuzzy inference system approach

    Directory of Open Access Journals (Sweden)

    Xiufang Lin

    2016-08-01

    Full Text Available Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads. However, the damping force cannot be controlled directly due to the inherent nonlinear characteristics of the magnetorheological dampers. Therefore, for fully exploiting the capabilities of the magnetorheological dampers, one of the challenging aspects is to develop an accurate inverse model which can appropriately predict the input voltage to control the damping force. In this article, a hybrid modeling strategy combining shuffled frog-leaping algorithm and adaptive-network-based fuzzy inference system is proposed to model the inverse dynamic characteristics of the magnetorheological dampers for improving the modeling accuracy. The shuffled frog-leaping algorithm is employed to optimize the premise parameters of the adaptive-network-based fuzzy inference system while the consequent parameters are tuned by a least square estimation method, here known as shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach. To evaluate the effectiveness of the proposed approach, the inverse modeling results based on the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach are compared with those based on the adaptive-network-based fuzzy inference system and genetic algorithm–based adaptive-network-based fuzzy inference system approaches. Analysis of variance test is carried out to statistically compare the performance of the proposed methods and the results demonstrate that the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system strategy outperforms the other two methods in terms of modeling (training accuracy and checking accuracy.

  13. A Selection Model to Logistic Centers Based on TOPSIS and MCGP Methods: The Case of Airline Industry

    Directory of Open Access Journals (Sweden)

    Kou-Huang Chen

    2014-01-01

    Full Text Available The location selection of a logistics center is a crucial decision relating to cost and benefit analysis in airline industry. However, it is difficult to be solved because there are many conflicting and multiple objectives in location problems. To solve the problem, this paper integrates fuzzy technique for order preference by similarity to an ideal solution (TOPSIS and multichoice goal programming (MCGP to obtain an appropriate logistics center from many alternative locations for airline industry. The proposed method in this paper will offer the decision makers (DMs to set multiple aspiration levels for the decision criteria. A numerical example of application is also presented.

  14. Fault Estimation for Fuzzy Delay Systems: A Minimum Norm Least Squares Solution Approach.

    Science.gov (United States)

    Huang, Sheng-Juan; Yang, Guang-Hong

    2017-09-01

    This paper mainly focuses on the problem of fault estimation for a class of Takagi-Sugeno fuzzy systems with state delays. A minimum norm least squares solution (MNLSS) approach is first introduced to establish a fault estimation compensator, which is able to optimize the fault estimator. Compared with most of the existing fault estimation methods, the MNLSS-based fault estimation method can effectively decrease the effect of state errors on the accuracy of fault estimation. Finally, three examples are given to illustrate the effectiveness and merits of the proposed method.

  15. Analysis Of A Neuro-Fuzzy Approach Of Air Pollution: Building A Case Study

    Directory of Open Access Journals (Sweden)

    Ciprian-Daniel NEAGU

    2001-12-01

    Full Text Available This work illustrates the necessity of an Artificial Intelligence (AI-based approach of air quality in urban and industrial areas. Some related results of Artificial Neural Networks (ANNs and Fuzzy Logic (FL for environmental data are considered: ANNs are proposed to the problem of short-term predicting of air pollutant concentrations in urban/industrial areas, with a special focus in the south-eastern Romania. The problems of designing a database about air quality in an urban/industrial area are discussed. First results confirm ANNs as an improvement of classical models and show the utility of ANNs in a well built air monitoring center.

  16. Adaptive control of discrete-time chaotic systems: a fuzzy control approach

    International Nuclear Information System (INIS)

    Feng Gang; Chen Guanrong

    2005-01-01

    This paper discusses adaptive control of a class of discrete-time chaotic systems from a fuzzy control approach. Using the T-S model of discrete-time chaotic systems, an adaptive control algorithm is developed based on some conventional adaptive control techniques. The resulting adaptively controlled chaotic system is shown to be globally stable, and its robustness is discussed. A simulation example of the chaotic Henon map control is finally presented, to illustrate an application and the performance of the proposed control algorithm

  17. Dynamic fuzzy cognitive network approach for modelling and control of PEM fuel cell for power electric bicycle system

    International Nuclear Information System (INIS)

    Kheirandish, Azadeh; Motlagh, Farid; Shafiabady, Niusha; Dahari, Mahidzal; Khairi Abdul Wahab, Ahmad

    2017-01-01

    Highlights: •Fuzzy cognitive map was proposed for the first time to describe the behaviour of fuel cell electric bicycle system. •Fuzzy rules were applied to explain the cause and effect between concepts. •To predict and analyse the cognitive map involved in the negotiation process. -- Abstract: Modelling Proton Exchange Membrane Fuel Cell (PEMFC) is the fundamental step in designing efficient systems for achieving higher performance. Among the development of new energy technologies, modelling and optimization of energy processes with pollution reduction, sufficient efficiency and low emission are considered one of the most promising areas of study. Despite affecting factors in PEMFC functionality, providing a reliable model for PEMFC is the key of performance optimization challenge. In this paper, fuzzy cognitive map has been used for modelling PEMFC system that is directed to provide a dynamic cognitive map from the affecting factors of the system. Controlling and modification of the system performance in various conditions is more practical by correlations among the performance factors of the PEMFC derived from fuzzy cognitive maps. On the other hand, the information of fuzzy cognitive map modelling is applicable for modification of neural networks structure for providing more accurate results based on the extracted knowledge from the cognitive map and visualization of the system’s performance. Finally, a rule based fuzzy cognitive map has been used that can be implemented for decision-making to control the system. This rule-based approach provides interpretability while enhancing the performance of the overall system.

  18. Intelligent fuzzy approach for fast fractal image compression

    Science.gov (United States)

    Nodehi, Ali; Sulong, Ghazali; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah; Rehman, Amjad; Saba, Tanzila

    2014-12-01

    Fractal image compression (FIC) is recognized as a NP-hard problem, and it suffers from a high number of mean square error (MSE) computations. In this paper, a two-phase algorithm was proposed to reduce the MSE computation of FIC. In the first phase, based on edge property, range and domains are arranged. In the second one, imperialist competitive algorithm (ICA) is used according to the classified blocks. For maintaining the quality of the retrieved image and accelerating algorithm operation, we divided the solutions into two groups: developed countries and undeveloped countries. Simulations were carried out to evaluate the performance of the developed approach. Promising results thus achieved exhibit performance better than genetic algorithm (GA)-based and Full-search algorithms in terms of decreasing the number of MSE computations. The number of MSE computations was reduced by the proposed algorithm for 463 times faster compared to the Full-search algorithm, although the retrieved image quality did not have a considerable change.

  19. Comparison of Customer Preference for Bulk Material Handling Equipment through Fuzzy-AHP Approach

    Science.gov (United States)

    Sen, Kingshuk; Ghosh, Surojit; Sarkar, Bijan

    2017-06-01

    In the present study, customer's perception has played one of the important roles for selection of the exact equipment out of available alternatives. The present study is dealt with the method of optimization of selection criteria of a material handling equipment, based on the technical specifications considered to be available at the user end. In this work, the needs of customers have been identified and prioritized, that lead to the selection of number of criteria, which have direct effect upon the performance of the equipment. To check the consistency of selection criteria, first of all an AHP based methodology is adopted with the identified criteria and available product categories, based upon which, the judgments of the users are defined to derive the priority scales. Such judgments expressed the relative strength or intensity of the impact of the elements of the hierarchy. Subsequently, all the alternatives have ranked for each identified criteria with subsequent constitution of weighted matrices. The same has been compared with the normalized values of approximate selling prices of the equipments to determine individual cost-benefit ratio. Based on the cost-benefit ratio, the equipment is ranked. With same conditions, the study is obtained again with a Fuzzy AHP concept, where a fuzzy linguistic approach has reduced the amount of uncertainty in decision making, caused by conventional AHP due to lack of deterministic approach. The priority vectors of category and criteria are determined separately and multiplied to obtain composite score. Subsequently, the average of fuzzy weights was determined and the preferences of equipment are ranked.

  20. Construction safety monitoring based on the project's characteristic with fuzzy logic approach

    Science.gov (United States)

    Winanda, Lila Ayu Ratna; Adi, Trijoko Wahyu; Anwar, Nadjadji; Wahyuni, Febriana Santi

    2017-11-01

    Construction workers accident is the highest number compared with other industries and falls are the main cause of fatal and serious injuries in high rise projects. Generally, construction workers accidents are caused by unsafe act and unsafe condition that can occur separately or together, thus a safety monitoring system based on influencing factors is needed to achieve zero accident in construction industry. The dynamic characteristic in construction causes high mobility for workers while doing the task, so it requires a continuously monitoring system to detect unsafe condition and to protect workers from potential hazards. In accordance with the unique nature of project, fuzzy logic approach is one of the appropriate methods for workers safety monitoring on site. In this study, the focus of discussion is based on the characteristic of construction projects in analyzing "potential hazard" and the "protection planning" to be used in accident prevention. The data have been collected from literature review, expert opinion and institution of safety and health. This data used to determine hazard identification. Then, an application model is created using Delphi programming. The process in fuzzy is divided into fuzzification, inference and defuzzification, according to the data collection. Then, the input and final output data are given back to the expert for assessment as a validation of application model. The result of the study showed that the potential hazard of construction workers accident could be analysed based on characteristic of project and protection system on site and fuzzy logic approach can be used for construction workers accident analysis. Based on case study and the feedback assessment from expert, it showed that the application model can be used as one of the safety monitoring tools.

  1. Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process

    Science.gov (United States)

    Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

    2018-03-01

    Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.

  2. Detection and classification of interstitial lung diseases and emphysema using a joint morphological-fuzzy approach

    Science.gov (United States)

    Chang Chien, Kuang-Che; Fetita, Catalin; Brillet, Pierre-Yves; Prêteux, Françoise; Chang, Ruey-Feng

    2009-02-01

    Multi-detector computed tomography (MDCT) has high accuracy and specificity on volumetrically capturing serial images of the lung. It increases the capability of computerized classification for lung tissue in medical research. This paper proposes a three-dimensional (3D) automated approach based on mathematical morphology and fuzzy logic for quantifying and classifying interstitial lung diseases (ILDs) and emphysema. The proposed methodology is composed of several stages: (1) an image multi-resolution decomposition scheme based on a 3D morphological filter is used to detect and analyze the different density patterns of the lung texture. Then, (2) for each pattern in the multi-resolution decomposition, six features are computed, for which fuzzy membership functions define a probability of association with a pathology class. Finally, (3) for each pathology class, the probabilities are combined up according to the weight assigned to each membership function and two threshold values are used to decide the final class of the pattern. The proposed approach was tested on 10 MDCT cases and the classification accuracy was: emphysema: 95%, fibrosis/honeycombing: 84% and ground glass: 97%.

  3. A Fuzzy-FMEA Risk Assessment Approach for Offshore Wind Turbines

    Directory of Open Access Journals (Sweden)

    M. Shafiee

    2013-01-01

    Full Text Available Failure Mode and Effects Analysis (FMEA has been extensively used by wind turbine assembly manufacturers for risk and reliability analysis. However, several limitations are associated with its implementation in offshore windfarms: (i the failure data gathered from SCADA system is often missing or unreliable, and hence, the assessment information of the three risk factors (i.e., severity, occurrence, and fault detection are mainly based onexperts’ knowledge; (ii it is rather difficult for experts to precisely evaluate the risk factors; (iii the relative importance among the risk factors is not taken into consideration, and hence, the results may not necessarily represent the true risk priorities; and etc. To overcome these drawbacks and improve the effectiveness of the traditional FMEA, we develop a fuzzy-FMEA approach for risk and failure mode analysis in offshore wind turbine systems. The information obtained from the experts is expressed using fuzzy linguistics terms, and a grey theory analysis is proposed to incorporate the relative importance of the riskfactors into the determination of risk priority of failure modes. The proposed approach is applied to an offshore wind turbine system with sixteen mechanical, electrical and auxiliary assemblies, and the results are compared with the traditional FMEA.

  4. Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

    Directory of Open Access Journals (Sweden)

    L. C. Félix-Herrán

    2015-01-01

    Full Text Available This work presents a novel semiactive model of a one-half lateral vehicle suspension. The contribution of this research is the inclusion of actuator dynamics (two magnetorheological nonlinear dampers in the modelling, which means that more realistic outcomes will be obtained, because, in real life, actuators have physical limitations. Takagi-Sugeno (T-S fuzzy approach is applied to a four-degree-of-freedom (4-DOF lateral one-half vehicle suspension. The system has two magnetorheological (MR dampers, whose numerical values come from a real characterization. T-S allows handling suspension’s components and actuator’s nonlinearities (hysteresis, saturation, and viscoplasticity by means of a set of linear subsystems interconnected via fuzzy membership functions. Due to their linearity, each subsystem can be handled with the very well-known control theory, for example, stability and performance indexes (this is an advantage of the T-S approach. To the best of authors’ knowledge, reported work does not include the aforementioned nonlinearities in the modelling. The generated model is validated via a case of study with simulation results. This research is paramount because it introduces a more accurate (the actuator dynamics, a complex nonlinear subsystem model that could be applied to one-half vehicle suspension control purposes. Suspension systems are extremely important for passenger comfort and stability in ground vehicles.

  5. Green Supplier Evaluation by Using an Integrated Fuzzy AHP- VIKOR Approach

    Directory of Open Access Journals (Sweden)

    Mehdi HakimiAsl

    2016-08-01

    Full Text Available In the previous decade, fossil energy resources shortage and environmental challenges such as air and water pollution, global warming, and greenhouse-gas emissions, etc. have increased environmental concerns considerably. Since, one of the most practical and useful solutions to decrease environmental pollutants is to deploy green purchasing and clean energies by organizations or even governments. Thus, the construction of renewable-energy power plants and, consequently, the green supplier selection for these plants’ equipment has become more important. With this respect, this article presents a novel approach to assess and select green suppliers of a solar power plant. The proposed approach integrates Fuzzy Analytic Hierarchy Process and VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje methodologies. The results demonstrate the efficiency of the proposed approach as a practical tool to assist managers and CEOs (Chief Executive Officers of electric power industry in assessing suppliers of solar power plant’s equipment.

  6. A new systematic and quantitative approach to characterization of surface nanostructures using fuzzy logic

    Science.gov (United States)

    Al-Mousa, Amjed A.

    Thin films are essential constituents of modern electronic devices and have a multitude of applications in such devices. The impact of the surface morphology of thin films on the device characteristics where these films are used has generated substantial attention to advanced film characterization techniques. In this work, we present a new approach to characterize surface nanostructures of thin films by focusing on isolating nanostructures and extracting quantitative information, such as the shape and size of the structures. This methodology is applicable to any Scanning Probe Microscopy (SPM) data, such as Atomic Force Microscopy (AFM) data which we are presenting here. The methodology starts by compensating the AFM data for some specific classes of measurement artifacts. After that, the methodology employs two distinct techniques. The first, which we call the overlay technique, proceeds by systematically processing the raster data that constitute the scanning probe image in both vertical and horizontal directions. It then proceeds by classifying points in each direction separately. Finally, the results from both the horizontal and the vertical subsets are overlaid, where a final decision on each surface point is made. The second technique, based on fuzzy logic, relies on a Fuzzy Inference Engine (FIE) to classify the surface points. Once classified, these points are clustered into surface structures. The latter technique also includes a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and then tune the fuzzy technique system uniquely for that surface. Both techniques have been applied to characterize organic semiconductor thin films of pentacene on different substrates. Also, we present a case study to demonstrate the effectiveness of our methodology to identify quantitatively particle sizes of two specimens of gold nanoparticles of different nominal dimensions dispersed on a mica surface. A comparison

  7. Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys

    Directory of Open Access Journals (Sweden)

    Gupta Neha

    2016-01-01

    Full Text Available In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP, and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP. A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran’s compromise allocation, Chatterjee’s compromise allocation and Khowaja’s compromise allocation is made to demonstrate the utility of the approach.

  8. Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

    Science.gov (United States)

    Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

    2015-08-01

    The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

  9. Control of a hydraulic system by means of a fuzzy approach

    Directory of Open Access Journals (Sweden)

    Mohamed Ksantini

    2013-07-01

    Full Text Available Non linear models can be represented conveniently by Takagi-Sugeno fuzzy models when nonlinearities are bounded. This approach uses a collection of linear models which are interpolated by non linear functions. Then the global control law is the interpolation by the same functions of each feedback associated to each linear model. A Lyapunov approach enables to compute these feedback gains. The number of linear models depends directly on the number of nonlinearities the system has. The more models there are, the more difficult it is to guarantee the stability of the closed loop. This paper proposes a method to reduce the number of linear models by assuming a number of nonlinearities considered as uncertainties and to guarantee the global exponential stability of the system. This method is applied on a hydraulic system.

  10. Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach

    Science.gov (United States)

    Arnett, Timothy; Cook, Brandon; Clark, Matthew A.; Rattan, Kuldip

    2017-01-01

    While many widely accepted methods and techniques exist for validation and verification of traditional controllers, at this time no solutions have been accepted for Fuzzy Logic Controllers (FLCs). Due to the highly nonlinear nature of such systems, and the fact that developing a valid FLC does not require a mathematical model of the system, it is quite difficult to use conventional techniques to prove controller stability. Since safety-critical systems must be tested and verified to work as expected for all possible circumstances, the fact that FLC controllers cannot be tested to achieve such requirements poses limitations on the applications for such technology. Therefore, alternative methods for verification and validation of FLCs needs to be explored. In this study, a novel approach using formal verification methods to ensure the stability of a FLC is proposed. Main research challenges include specification of requirements for a complex system, conversion of a traditional FLC to a piecewise polynomial representation, and using a formal verification tool in a nonlinear solution space. Using the proposed architecture, the Fuzzy Logic Controller was found to always generate negative feedback, but inconclusive for Lyapunov stability.

  11. Classifying Human Activity Patterns from Smartphone Collected GPS data: a Fuzzy Classification and Aggregation Approach.

    Science.gov (United States)

    Wan, Neng; Lin, Ge

    2016-12-01

    Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone-measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone-collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g., up to 96% in activity identification) with use of this method. Two examples were provided in the appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.

  12. Sensory evaluation of selected formulated milk barberry drinks using the fuzzy approach.

    Science.gov (United States)

    Tahsiri, Zahra; Niakousari, Mehrdad; Khoshnoudi-Nia, Sara; Hosseini, Seyed Mohamad H

    2017-05-01

    Amid rigid competition in marketing to accomplish customers' needs, the cost of disappointment is too high. In an effort to escape market disappointment, one of the options to be considered is probing for customer satisfaction through sensory evaluation. This study aims to rank the six selected milk-barberry drink formulae out of 24 (code numbers S3, S4, S15, S16, S17 and S18) each having different milk:barberry:pectin amount (7: 3: 0.2; 6: 4: 0.2; 7: 3: 0.4, 6: 4: 0.4, 5: 5: 0.4 and 6: 4: 0.4), respectively, and to determine the best of quality attribute through sensory evaluation, using the fuzzy decision-making model. The selection was based on pH, total solid content, and degree of serum separation and rheological properties of the drinks. The results showed that the S4 had the highest acceptability, rated under the "very good" category, whereas the lowest acceptability was reported for the S3 which was classified under the "satisfactory" category. In summary, the ranking of the milk-barberry drinks was S4 >  S17 >  S16 >  S15 >  S18 >  S3. Furthermore, quality attributes were ranked as taste > mouth feel > aroma > color. Results suggest that the fuzzy approach could be appropriately used to evaluate this type of sensory data.

  13. Performance of fuzzy approach in Malaysia short-term electricity load forecasting

    Science.gov (United States)

    Mansor, Rosnalini; Zulkifli, Malina; Yusof, Muhammad Mat; Ismail, Mohd Isfahani; Ismail, Suzilah; Yin, Yip Chee

    2014-12-01

    Many activities such as economic, education and manafucturing would paralyse with limited supply of electricity but surplus contribute to high operating cost. Therefore electricity load forecasting is important in order to avoid shortage or excess. Previous finding showed festive celebration has effect on short-term electricity load forecasting. Being a multi culture country Malaysia has many major festive celebrations such as Eidul Fitri, Chinese New Year and Deepavali but they are moving holidays due to non-fixed dates on the Gregorian calendar. This study emphasis on the performance of fuzzy approach in forecasting electricity load when considering the presence of moving holidays. Autoregressive Distributed Lag model was estimated using simulated data by including model simplification concept (manual or automatic), day types (weekdays or weekend), public holidays and lags of electricity load. The result indicated that day types, public holidays and several lags of electricity load were significant in the model. Overall, model simplification improves fuzzy performance due to less variables and rules.

  14. Prescribed burning impact on forest soil properties--a Fuzzy Boolean Nets approach.

    Science.gov (United States)

    Castro, Ana C Meira; Paulo Carvalho, Joao; Ribeiro, S

    2011-02-01

    The Portuguese northern forests are often and severely affected by wildfires during the Summer season. These occurrences significantly affect and negatively impact all ecosystems, namely soil, fauna and flora. In order to reduce the occurrences of natural wildfires, some measures to control the availability of fuel mass are regularly implemented. Those preventive actions concern mainly prescribed burnings and vegetation pruning. This work reports on the impact of a prescribed burning on several forest soil properties, namely pH, soil moisture, organic matter content and iron content, by monitoring the soil self-recovery capabilities during a one year span. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, which was kept intact from prescribed burnings during a period of four years. Soil samples were collected from five plots at three different layers (0-3, 3-6 and 6-18) 1 day before prescribed fire and at regular intervals after the prescribed fire. This paper presents an approach where Fuzzy Boolean Nets (FBN) and Fuzzy reasoning are used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil properties. FBN were chosen due to the scarcity on available quantitative data. The results showed that soil properties were affected by prescribed burning practice and were unable to recover their initial values after one year. Copyright © 2010 Elsevier Inc. All rights reserved.

  15. Smart Pedestrian Crossing Management at Traffic Light Junctions through a Fuzzy-Based Approach

    Directory of Open Access Journals (Sweden)

    Giovanni Pau

    2018-02-01

    Full Text Available In the last few years, numerous research efforts have been conducted to merge the Internet of Things (IoT with smart city environments. The goal to make a city “smart” is arising as a possible solution to lessen the issues caused by the urban population growth and fast urbanization. Attention also has focused on the pedestrian crossings because they are one of the most dangerous places in the transport field. Information and Communications Technologies (ICT can undoubtedly be an excellent support in developing infrastructures that can best manage pedestrian crossing. For this reason, this paper introduces a fuzzy logic-based solution able to manage dynamically the traffic lights’ phases in signalized pedestrian crossings. The proposed approach provides the possibility to change the phases of the traffic light taking into account the time of the day and the number of pedestrians about to cross the road. The paper presents a thorough description of the fuzzy logic controller configuration, an in-depth analysis of the application scenario and simulative assessments obtained through Vissim simulations.

  16. Fuzzy Logic Approach for the Prediction of Dross Formation in CO2 Laser Cutting of Mild Steel

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2015-11-01

    Full Text Available Dross free laser cutting is very important in the application of laser cutting technology. This paper focuses on the development of a fuzzy logic model to predict dross formation in CO2 laser oxygen cutting of mild steel. Laser cutting experiment, conducted according to Taguchi’s experimental design using L25 orthogonal array, provided a set of data for the development of a fuzzy rule base. The predicting fuzzy logic model is based on using Mamdani-type inference system. Developed fuzzy logic model considered the cutting speed, laser power and assist gas pressure as inputs. Using this model the effects of the selected laser cutting parameters on the dross formation were investigated. Additionally, 3-D surface plots were generated to study the interaction effects of the laser cutting parameters. The analysis revealed that the cutting speed has the most significant effect, followed by laser power and assist gas pressure. The results indicated that the fuzzy logic modeling approach can be effectively used for the dross formation prediction in CO2 laser cutting of mild steel.

  17. Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

    Institute of Scientific and Technical Information of China (English)

    FENG Yu-hu

    2005-01-01

    By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

  18. A multicriteria decision making approach based on fuzzy theory and credibility mechanism for logistics center location selection.

    Science.gov (United States)

    Wang, Bowen; Xiong, Haitao; Jiang, Chengrui

    2014-01-01

    As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

  19. A New Method Based on TOPSIS and Response Surface Method for MCDM Problems with Interval Numbers

    Directory of Open Access Journals (Sweden)

    Peng Wang

    2015-01-01

    Full Text Available As the preference of design maker (DM is always ambiguous, we have to face many multiple criteria decision-making (MCDM problems with interval numbers in our daily life. Though there have been some methods applied to solve this sort of problem, it is always complex to comprehend and sometimes difficult to implement. The calculation processes are always ineffective when a new alternative is added or removed. In view of the weakness like this, this paper presents a new method based on TOPSIS and response surface method (RSM for MCDM problems with interval numbers, RSM-TOPSIS-IN for short. The key point of this approach is the application of deviation degree matrix, which ensures that the DM can get a simple response surface (RS model to rank the alternatives. In order to demonstrate the feasibility and effectiveness of the proposed method, three illustrative MCMD problems with interval numbers are analysed, including (a selection of investment program, (b selection of a right partner, and (c assessment of road transport technologies. The contrast of ranking results shows that the RSM-TOPSIS-IN method is in good agreement with those derived by earlier researchers, indicating it is suitable to solve MCDM problems with interval numbers.

  20. Identification and Ranking of Critical Success Factors of Knowledge Management Using Fuzzy Quality Function Deployment Approach: A Case Study

    Directory of Open Access Journals (Sweden)

    Ali Mohaghar

    2014-02-01

    Based on the information accessible for the researchers, this is one of the first works which evaluates the key factors of successful knowledge management through fuzzy quality function deployment approach. It is expected that the proposed method would represent appropriate tools for enterprises which have decided to implement knowledge management because it prioritizes the critical success factors based on the knowledge management outcomes.

  1. A Fuzzy Modeling Approach to Road Transport with Application to a Case of Spent Nuclear Fuel Transport

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Bianchi, Mauro

    2004-01-01

    In this paper, we propose a general fuzzy inference approach to building a model of hazardous road transport that relates given traffic, weather, and vehicle-speed conditions to the accident rate. The development of the model is discussed in detail, and its validation is provided with reference to literature data regarding the transport of spent nuclear fuel to its final confinement repository

  2. An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

    Directory of Open Access Journals (Sweden)

    Snezana Pavle Knezevic

    2017-09-01

    Full Text Available The aim of this paper is to apply an integrated model, which combines methods of classical and fuzzy Multi-criteria decision making (MCDM in selected six large equity companies from the Serbian energy sector. The data considered are retrieved from the official financial statements. Four main criteria were analyzed, identified by the previous researchers and pointing to the employees productivity: Operating income/Number of employees, Equity/Number of employees, Net income/Number of employees and Total assets/Number of employees. The contribution of this paper lies in the application of a hybrid model that integrates two MCDM methods: Fuzzy Analytic Hierarchy Process (FAHP and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS to analyse the employee productivity in selected D-Electrical power supply companies operating in Serbia. The FAHP is an effective method for mathematical representation of uncertain and imprecise evaluations made by humans, while the TOPSIS method is an efficient way to rank the alternatives. Results show that operating income is of highest importance for estimating employee productivity and decision making, while equity is of the weakest. Furthermore, the most productive operations in large enterprises from selected companies of the sector D-Electrical power supply are found in the company PC EPS Beograd, and the lowest are in the ED Center llc Kragujevac.

  3. Using an Integrated Group Decision Method Based on SVM, TFN-RS-AHP, and TOPSIS-CD for Cloud Service Supplier Selection

    Directory of Open Access Journals (Sweden)

    Lian-hui Li

    2017-01-01

    Full Text Available To solve the cloud service supplier selection problem under the background of cloud computing emergence, an integrated group decision method is proposed. The cloud service supplier selection index framework is built from two perspectives of technology and technology management. Support vector machine- (SVM- based classification model is applied for the preliminary screening to reduce the number of candidate suppliers. A triangular fuzzy number-rough sets-analytic hierarchy process (TFN-RS-AHP method is designed to calculate supplier’s index value by expert’s wisdom and experience. The index weight is determined by criteria importance through intercriteria correlation (CRITIC. The suppliers are evaluated by the improved TOPSIS replacing Euclidean distance with connection distance (TOPSIS-CD. An electric power enterprise’s case is given to illustrate the correctness and feasibility of the proposed method.

  4. Optimal Decision-Making in Fuzzy Economic Order Quantity (EOQ Model under Restricted Space: A Non-Linear Programming Approach

    Directory of Open Access Journals (Sweden)

    M. Pattnaik

    2013-08-01

    Full Text Available In this paper the concept of fuzzy Non-Linear Programming Technique is applied to solve an economic order quantity (EOQ model under restricted space. Since various types of uncertainties and imprecision are inherent in real inventory problems they are classically modeled using the approaches from the probability theory. However, there are uncertainties that cannot be appropriately treated by usual probabilistic models. The questions how to define inventory optimization tasks in such environment how to interpret optimal solutions arise. This paper allows the modification of the Single item EOQ model in presence of fuzzy decision making process where demand is related to the unit price and the setup cost varies with the quantity produced/Purchased. This paper considers the modification of objective function and storage area in the presence of imprecisely estimated parameters. The model is developed for the problem by employing different modeling approaches over an infinite planning horizon. It incorporates all concepts of a fuzzy arithmetic approach, the quantity ordered and the demand per unit compares both fuzzy non linear and other models. Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated through an example problem and ugh MATLAB (R2009a version software, the two and three dimensional diagrams are represented to the application. Sensitivity analysis of the optimal solution is also studied with respect to changes in different parameter values and to draw managerial insights of the decision problem.

  5. A MOORA based fuzzy multi-criteria decision making approach for supply chain strategy selection

    Directory of Open Access Journals (Sweden)

    Bijan Sarkar

    2012-08-01

    Full Text Available To acquire the competitive advantages in order to survive in the global business scenario, modern companies are now facing the problems of selecting key supply chain strategies. Strategy selection becomes difficult as the number of alternatives and conflicting criteria increases. Multi criteria decision making (MCDM methodologies help the supply chain managers take a lead in a complex industrial set-up. The present investigation applies fuzzy MCDM technique entailing multi-objective optimization on the basis of ratio analysis (MOORA in selection of alternatives in a supply chain. The MOORA method is utilized to three suitable numerical examples for the selection of supply chain strategies (warehouse location selection and vendor/supplier selection. The results obtained by using current approach almost match with those of previous research works published in various open journals. The empirical study has demonstrated the simplicity and applicability of this method as a strategic decision making tool in a supply chain.

  6. Test interval optimization of safety systems of nuclear power plant using fuzzy-genetic approach

    International Nuclear Information System (INIS)

    Durga Rao, K.; Gopika, V.; Kushwaha, H.S.; Verma, A.K.; Srividya, A.

    2007-01-01

    Probabilistic safety assessment (PSA) is the most effective and efficient tool for safety and risk management in nuclear power plants (NPP). PSA studies not only evaluate risk/safety of systems but also their results are very useful in safe, economical and effective design and operation of NPPs. The latter application is popularly known as 'Risk-Informed Decision Making'. Evaluation of technical specifications is one such important application of Risk-Informed decision making. Deciding test interval (TI), one of the important technical specifications, with the given resources and risk effectiveness is an optimization problem. Uncertainty is inherently present in the availability parameters such as failure rate and repair time due to the limitation in assessing these parameters precisely. This paper presents a solution to test interval optimization problem with uncertain parameters in the model with fuzzy-genetic approach along with a case of application from a safety system of Indian pressurized heavy water reactor (PHWR)

  7. Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

    Science.gov (United States)

    Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

    2017-04-01

    Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial

  8. Surface Roughness of Al-5Cu Alloy using a Taguchi-Fuzzy Based Approach

    Directory of Open Access Journals (Sweden)

    Biswajit Das

    2014-07-01

    Full Text Available The present paper investigates the application of traditional Taguchi method with fuzzy logic for multi objective optimization of the turning process of Al-5Cu alloy in CNC Lathe machine. The cutting parameters are optimized with considerations of the multiple surface roughness characteristics (Centre line average roughness Ra, Average maximum height of the profile Rz, Maximum height of the profile Rt, Mean spacing of local peaks of the profile Sa . Experimental results are demonstrated to present the effectiveness of this approach. The parameters used in the experiment were cutting speed, depth of cut, feed rate. Other parameters such as tool nose radius, tool material, workpiece length, workpiece diameter, and workpiece material were taken as constant.

  9. Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach

    DEFF Research Database (Denmark)

    Awasthi, Anjali; Govindan, Kannan; Gold, Stefan

    2018-01-01

    Politico-economic deregulation, new communication technologies, and cheap transport have pushed companies to increasingly outsource business activities to geographically distant countries. Such outsourcing has often resulted in complex supply chain configurations. Because social and environmental...... and global risk displayed the least weight. This result clearly shows that global risks are still not considered a major criterion for supplier selection. Further, the proposed framework may serve as a starting point for developing managerial decision-making tools to help companies more effectively address...... regulations in those countries are often weak or poorly enforced, stakeholders impose responsibility on focal companies to ensure socially and environmentally sustainable production standards throughout their supply chains. In this paper, we present an integrated fuzzy AHP-VIKOR approach-based framework...

  10. Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

    This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

  11. Identifying the critical financial ratios for stocks evaluation: A fuzzy delphi approach

    Science.gov (United States)

    Mokhtar, Mazura; Shuib, Adibah; Mohamad, Daud

    2014-12-01

    Stocks evaluation has always been an interesting and challenging problem for both researchers and practitioners. Generally, the evaluation can be made based on a set of financial ratios. Nevertheless, there are a variety of financial ratios that can be considered and if all ratios in the set are placed into the evaluation process, data collection would be more difficult and time consuming. Thus, the objective of this paper is to identify the most important financial ratios upon which to focus in order to evaluate the stock's performance. For this purpose, a survey was carried out using an approach which is based on an expert judgement, namely the Fuzzy Delphi Method (FDM). The results of this study indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share and debt to equity are the most important ratios.

  12. A Dynamic Fuzzy Approach Based on the EDAS Method for Multi-Criteria Subcontractor Evaluation

    Directory of Open Access Journals (Sweden)

    Mehdi Keshavarz-Ghorabaee

    2018-03-01

    Full Text Available Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

  13. METHOD FOR SELECTION OF PROJECT MANAGEMENT APPROACH BASED ON FUZZY CONCEPTS

    Directory of Open Access Journals (Sweden)

    Igor V. KONONENKO

    2017-03-01

    Full Text Available Literature analysis of works that devoted to research of the selection a project management approach and development of effective methods for this problem solution is given. Mathematical model and method for selection of project management approach with fuzzy concepts of applicability of existing approaches are proposed. The selection is made of such approaches as the PMBOK Guide, the ISO21500 standard, the PRINCE2 methodology, the SWEBOK Guide, agile methodologies Scrum, XP, and Kanban. The number of project parameters which have a great impact on the result of the selection and measure of their impact is determined. Project parameters relate to information about the project, team, communication, critical project risks. They include the number of people involved in the project, the customer's experience with this project team, the project team's experience in this field, the project team's understanding of requirements, adapting ability, initiative, and others. The suggested method is considered on the example of its application for selection a project management approach to software development project.

  14. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  15. CAF: Cluster algorithm and a-star with fuzzy approach for lifetime enhancement in wireless sensor networks

    KAUST Repository

    Yuan, Y.; Li, C.; Yang, Y.; Zhang, Xiangliang; Li, L.

    2014-01-01

    Energy is a major factor in designing wireless sensor networks (WSNs). In particular, in the real world, battery energy is limited; thus the effective improvement of the energy becomes the key of the routing protocols. Besides, the sensor nodes are always deployed far away from the base station and the transmission energy consumption is index times increasing with the increase of distance as well. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of a clustering algorithm, a fuzzy approach, and an A-star method. The proposal is divided into two steps. Firstly, WSNs are separated into clusters using the Stable Election Protocol (SEP) method. Secondly, the combined methods of fuzzy inference and A-star algorithm are adopted, taking into account the factors such as the remaining power, the minimum hops, and the traffic numbers of nodes. Simulation results demonstrate that the proposed method has significant effectiveness in terms of balancing energy consumption as well as maximizing the network lifetime by comparing the performance of the A-star and fuzzy (AF) approach, cluster and fuzzy (CF)method, cluster and A-star (CA)method, A-star method, and SEP algorithm under the same routing criteria. 2014 Yali Yuan et al.

  16. A Fuzzy-AHP-QFD approach for achieving lean attributes for competitive advantages development, Case study: The Staam Sanat Company

    Directory of Open Access Journals (Sweden)

    Emad Roghanian

    2013-01-01

    Full Text Available As one of the new producing approaches, lean production has brought in new opportunities for producers all around the world. Many producers have adopted the technique for surviving the growing world market. By combining competitive advantages, lean attributes, and lean enablers as three factors, the present study attempts to determine the most suitable enablers for improvement of lean attributes in a case study. Quality Function Deployment (QFD in fuzzy environment and House of Quality (HOQ matrix, successfully employed for development of new products, are adopted as approach of the study. Weights of competitive advantages, lean attributes and enablers are calculated through fuzzy analysis hierarchy process (FAHP, while fuzzy logarithmic least square method (LLSM is used in calculation of the weights. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, final ranking of lean enablers is represented through area ranking method and taking into account various techniques of decision makers’ risk. Finally, a case study in automotive industry is introduced to demonstrate the implementation of the proposed methodology.

  17. CAF: Cluster algorithm and a-star with fuzzy approach for lifetime enhancement in wireless sensor networks

    KAUST Repository

    Yuan, Y.

    2014-04-28

    Energy is a major factor in designing wireless sensor networks (WSNs). In particular, in the real world, battery energy is limited; thus the effective improvement of the energy becomes the key of the routing protocols. Besides, the sensor nodes are always deployed far away from the base station and the transmission energy consumption is index times increasing with the increase of distance as well. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of a clustering algorithm, a fuzzy approach, and an A-star method. The proposal is divided into two steps. Firstly, WSNs are separated into clusters using the Stable Election Protocol (SEP) method. Secondly, the combined methods of fuzzy inference and A-star algorithm are adopted, taking into account the factors such as the remaining power, the minimum hops, and the traffic numbers of nodes. Simulation results demonstrate that the proposed method has significant effectiveness in terms of balancing energy consumption as well as maximizing the network lifetime by comparing the performance of the A-star and fuzzy (AF) approach, cluster and fuzzy (CF)method, cluster and A-star (CA)method, A-star method, and SEP algorithm under the same routing criteria. 2014 Yali Yuan et al.

  18. An Approach for Environment Mapping and Control of Wall Follower Cellbot Through Monocular Vision and Fuzzy System

    OpenAIRE

    Farias, Karoline de M.; Rodrigues Junior, WIlson Leal; Bezerra Neto, Ranulfo P.; Rabelo, Ricardo A. L.; Santana, Andre M.

    2017-01-01

    This paper presents an approach using range measurement through homography calculation to build 2D visual occupancy grid and control the robot through monocular vision. This approach is designed for a Cellbot architecture. The robot is equipped with wall following behavior to explore the environment, which enables the robot to trail objects contours, residing in the fuzzy control the responsibility to provide commands for the correct execution of the robot movements while facing the advers...

  19. Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach

    International Nuclear Information System (INIS)

    Kisi, Ozgur

    2014-01-01

    The study investigates the ability of FG (fuzzy genetic) approach in modeling solar radiation of seven cities from Mediterranean region of Anatolia, Turkey. Latitude, longitude, altitude and month of the year data from the Adana, K. Maras, Mersin, Antalya, Isparta, Burdur and Antakya cities are used as inputs to the FG model to estimate one month ahead solar radiation. FG model is compared with ANNs (artificial neural networks) and ANFIS (adaptive neruro fuzzzy inference system) models with respect to RMSE (root mean square errors), MAE (mean absolute errors) and determination coefficient (R 2 ) statistics. Comparison results indicate that the FG model performs better than the ANN and ANFIS models. It is found that the FG model can be successfully used for estimating solar radiation by using latitude, longitude, altitude and month of the year information. FG model with RMSE = 6.29 MJ/m 2 , MAE = 4.69 MJ/m 2 and R 2 = 0.905 in the test stage was found to be superior to the optimal ANN model with RMSE = 7.17 MJ/m 2 , MAE = 5.29 MJ/m 2 and R 2 = 0.876 and ANFIS model with RMSE = 6.75 MJ/m 2 , MAE = 5.10 MJ/m 2 and R 2 = 0.892 in estimating solar radiation. - Highlights: • SR (Solar radiation) of seven cities from Mediterranean region of Turkey is predicted. • FG (Fuzzy genetic) models are developed for accurately estimation of SR. • The ability of the FG models used in the study is found to be satisfactory. • FG models are compared with commonly used ANNs (artificial neural networks). • FG models are found to perform better than the ANNs models

  20. Evaluation of Groundwater Remediation Technologies Based on Fuzzy Multi-Criteria Decision Analysis Approaches

    Directory of Open Access Journals (Sweden)

    Hao Wang

    2017-06-01

    Full Text Available Petroleum is an essential resource for the development of society and its production is huge. There is a great risk of leakage of oil during production, refining, and transportation. After entering the environment, the oil pollutants will be a great threat to the environment and may endanger human health. Therefore, it is very important to remediate oil pollution in the subsurface. However, it is necessary to choose the appropriate remediation technology. In this paper, 18 technologies are evaluated through constructing a parameter matrix with each technology and seven performance indicators, and a comprehensive analysis model is presented. In this model, four MCDA methods are used. They are SWA (Simple Weighted Addition Method, WP (Weighted Product Method, CGT (Cooperative Game Theory, and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution. Mean ranking and Borda ranking methods are used to integrate the results of SWA, WP, CGT, and TOPSIS. Then two selection priorities of each method (mean ranking and Borda ranking are obtained. The model is proposed to help decide the best choice of remediation technologies. It can effectively reduce contingency, subjectivity, one-sidedness of the traditional methods and provide scientific reference for effective decision-making.

  1. An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules.

    Science.gov (United States)

    Topuz, Emel; van Gestel, Cornelis A M

    2016-01-01

    The usage of Engineered Nanoparticles (ENPs) in consumer products is relatively new and there is a need to conduct environmental risk assessment (ERA) to evaluate their impacts on the environment. However, alternative approaches are required for ERA of ENPs because of the huge gap in data and knowledge compared to conventional pollutants and their unique properties that make it difficult to apply existing approaches. This study aims to propose an ERA approach for ENPs by integrating Analytical Hierarchy Process (AHP) and fuzzy inference models which provide a systematic evaluation of risk factors and reducing uncertainty about the data and information, respectively. Risk is assumed to be the combination of occurrence likelihood, exposure potential and toxic effects in the environment. A hierarchy was established to evaluate the sub factors of these components. Evaluation was made with fuzzy numbers to reduce uncertainty and incorporate the expert judgements. Overall score of each component was combined with fuzzy inference rules by using expert judgements. Proposed approach reports the risk class and its membership degree such as Minor (0.7). Therefore, results are precise and helpful to determine the risk management strategies. Moreover, priority weights calculated by comparing the risk factors based on their importance for the risk enable users to understand which factor is effective on the risk. Proposed approach was applied for Ag (two nanoparticles with different coating) and TiO2 nanoparticles for different case studies. Results verified the proposed benefits of the approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. New Models for Forecasting Enrollments: Fuzzy Time Series and Neural Network Approaches.

    Science.gov (United States)

    Song, Qiang; Chissom, Brad S.

    Since university enrollment forecasting is very important, many different methods and models have been proposed by researchers. Two new methods for enrollment forecasting are introduced: (1) the fuzzy time series model; and (2) the artificial neural networks model. Fuzzy time series has been proposed to deal with forecasting problems within a…

  3. Fuzzeval: A Fuzzy Controller-Based Approach in Adaptive Learning for Backgammon Game

    DEFF Research Database (Denmark)

    Heinze, Mikael; Ortiz-Arroyo, Daniel; Larsen, Henrik Legind

    2005-01-01

    In this paper we investigate the effectiveness of applying fuzzy controllers to create strong computer player programs in the domain of backgammon. Fuzzeval, our proposed mechanism, consists of a fuzzy controller that dynamically evaluates the perceived strength of the board configurations it re-...

  4. Hybrid Type II fuzzy system & data mining approach for surface finish

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  5. A Novel Approach toward Fuzzy Generalized Bi-Ideals in Ordered Semigroups

    Directory of Open Access Journals (Sweden)

    Faiz Muhammad Khan

    2014-01-01

    Full Text Available In several advanced fields like control engineering, computer science, fuzzy automata, finite state machine, and error correcting codes, the use of fuzzified algebraic structures especially ordered semigroups plays a central role. In this paper, we introduced a new and advanced generalization of fuzzy generalized bi-ideals of ordered semigroups. These new concepts are supported by suitable examples. These new notions are the generalizations of ordinary fuzzy generalized bi-ideals of ordered semigroups. Several fundamental theorems of ordered semigroups are investigated by the properties of these newly defined fuzzy generalized bi-ideals. Further, using level sets, ordinary fuzzy generalized bi-ideals are linked with these newly defined ideals which is the most significant part of this paper.

  6. Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

    Science.gov (United States)

    Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

    2018-05-01

    Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2015-06-01

    Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

  8. Probabilistic and Fuzzy Arithmetic Approaches for the Treatment of Uncertainties in the Installation of Torpedo Piles

    Directory of Open Access Journals (Sweden)

    Denise Margareth Kazue Nishimura Kunitaki

    2008-01-01

    Full Text Available The “torpedo” pile is a foundation system that has been recently considered to anchor mooring lines and risers of floating production systems for offshore oil exploitation. The pile is installed in a free fall operation from a vessel. However, the soil parameters involved in the penetration model of the torpedo pile contain uncertainties that can affect the precision of analysis methods to evaluate its final penetration depth. Therefore, this paper deals with methodologies for the assessment of the sensitivity of the response to the variation of the uncertain parameters and mainly to incorporate into the analysis method techniques for the formal treatment of the uncertainties. Probabilistic and “possibilistic” approaches are considered, involving, respectively, the Monte Carlo method (MC and concepts of fuzzy arithmetic (FA. The results and performance of both approaches are compared, stressing the ability of the latter approach to efficiently deal with the uncertainties of the model, with outstanding computational efficiency, and therefore, to comprise an effective design tool.

  9. Application of fuzzy logic approach for wind erosion hazard mapping in Laghouat region (Algeria) using remote sensing and GIS

    Science.gov (United States)

    Saadoud, Djouher; Hassani, Mohamed; Martin Peinado, Francisco José; Guettouche, Mohamed Saïd

    2018-06-01

    Wind erosion is one of the most serious environmental problems in Algeria that threatens human activities and socio-economic development. The main goal of this study is to apply a fuzzy logic approach to wind erosion sensitivity mapping in the Laghouat region, Algeria. Six causative factors, obtained by applying fuzzy membership functions to each used parameter, are considered: soil, vegetation cover, wind factor, soil dryness, land topography and land cover sensitivity. Different fuzzy operators (AND, OR, SUM, PRODUCT, and GAMMA) are applied to generate wind-erosion hazard map. Success rate curves reveal that the fuzzy gamma (γ) operator, with γ equal to 0.9, gives the best prediction accuracy with an area under curve of 85.2%. The resulting wind-erosion sensitivity map delineates the area into different zones of five relative sensitivity classes: very high, high, moderate, low and very low. The estimated result was verified by field measurements and the high statistically significant value of a chi-square test.

  10. An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques

    Directory of Open Access Journals (Sweden)

    Amin Shahmardan

    2013-09-01

    Full Text Available Purpose: The intention of this paper is the presentation of a new integrated approach for solving a multi attribute decision making problem by the use of Entropy Fuzzy and F- PROMETHEE (fuzzy preference ranking method for enrichment evaluation techniques. Design/methodology/approach: In these sorts of multi attribute decision making problem, a number of criteria and alternatives are put forward as input data. Ranking of these alternatives according to mentioned criteria is regarded as the outcome of solving these kinds of problems. Initially, weights of criteria are determined by implementation of Entropy Fuzzy method. According to determined weights, F-PROMETHEE method is exerted to rank these alternatives in terms of desirability of DM (decision maker. Findings: Being in an uncertain environment and vagueness of DM’s judgments, lead us to implement an algorithm which can deal with these constraints properly. This technique namely called Entropy Fuzzy as a weighting method and F-PROMETHEE is performed to fulfill this approach more precisely according to tangible and intangible aspects. The main finding of applied approach is the final ranking of alternatives helping DM to have a more reliable decision. Originality/Value: The main contribution of this approach is the giving real significance to DM’s attitudes about mentioned criteria in determined alternatives which is not elucidate in former approaches like Analytical Hierarchy Process (AHP. Furthermore, previous methods like Shanon Entropy do not pay attention sufficiently to satisfaction degree of each criterion in proposed alternatives, regarding to DM’s statements. Comprehensive explanations about these procedures have been made in miscellaneous sections of this article.

  11. Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

    Directory of Open Access Journals (Sweden)

    Rana Dinesh Singh

    2015-01-01

    Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

  12. Fuzzy control and identification

    CERN Document Server

    Lilly, John H

    2010-01-01

    This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

  13. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    International Nuclear Information System (INIS)

    Lee, S.

    2009-01-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities

  14. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of). Energy Policy Research Division; Mogi, G. [Tokyo Univ., (Japan). Dept. of Technology Management for Innovation, Graduate School of Engineering; Kim, J. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of)

    2009-07-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities.

  15. Modeling the thermal behavior of fluid flow inside channels using an artificial locally linear neuro-fuzzy approach

    Directory of Open Access Journals (Sweden)

    Azadeh Hashemian

    2008-06-01

    Full Text Available Enhanced surface heat exchangers are commonly used all worldwide. If applicable, due to their complicated geometry, simulating corrugated plate heat exchangers is a time-consuming process. In the present study, first we simulate the heat transfer in a sharp V-shape corrugation cell with constant temperature walls; then, we use a Locally Linear Neuro-Fuzzy method based on a radial basis function (RBFs to model the temperature field in the whole channel. New approach is developed to deal with fast computational and low memory resources that can be used with the largest available data sets. The purpose of the research is to reveal the advantages of proposed Neuro-Fuzzy model as a powerful modeling system designed for predicting and to make a fair comparison between it and the successful FLUENT simulated approaches in its best structures.

  16. A FUZZY LOGIC-BASED APPROACH FOR THE DETECTION OF FLOODED VEGETATION BY MEANS OF SYNTHETIC APERTURE RADAR DATA

    Directory of Open Access Journals (Sweden)

    V. Tsyganskaya

    2016-06-01

    Full Text Available In this paper an algorithm designed to map flooded vegetation from synthetic aperture radar (SAR imagery is introduced. The approach is based on fuzzy logic which enables to deal with the ambiguity of SAR data and to integrate multiple ancillary data containing topographical information, simple hydraulic considerations and land cover information. This allows the exclusion of image elements with a backscatter value similar to flooded vegetation, to significantly reduce misclassification errors. The flooded vegetation mapping procedure is tested on a flood event that occurred in Germany over parts of the Saale catchment on January 2011 using a time series of high resolution TerraSAR-X data covering the time interval from 2009 to 2015. The results show that the analysis of multi-temporal X-band data combined with ancillary data using a fuzzy logic-based approach permits the detection of flooded vegetation areas.

  17. Synthesis of A Sustainable Sago-Based Value Chain via Fuzzy Optimisation Approach

    Directory of Open Access Journals (Sweden)

    Chong Jeffrey Hong Seng

    2018-01-01

    Full Text Available Sago starch is one of the staple foods for human, especially in Asia’s Region. It can be produced via sago starch extraction process (SSEP. During the SSEP, several types of sago wastes are generated such as sago fiber (SF, sago bark (SB and sago wastewater (SW. With the increase in production of existing factories and sago mills, the sago industrial practice in waste disposal management is gaining more attention, thus implementation of effective waste management is vital. One of the promising ways to have effective waste management is to create value out of the sago wastes. In a recent study, sago-based refinery, which is a facility to convert sago wastes into value-added products (e.g., bio-ethanol and energy was found feasible. However, the conversion of other value added products from sago wastes while considering the environmental impact has not been considered in sago value chain. Therefore, an optimum sago value chain, which involved conversion activities of sago wastes into value-added products, is aimed to be synthesised in this work. The optimum sago value chain will be evaluated based on profit and carbon emissions using fuzzy-based optimisation approach via a commercial optimisation software, Lingo 16.0. To illustrate the the developed approach, an industrial case study has been solved in this work.

  18. Fishmeal Supplier Evaluation and Selection for Aquaculture Enterprise Sustainability with a Fuzzy MCDM Approach

    Directory of Open Access Journals (Sweden)

    Tsung-Hsien Wu

    2017-11-01

    Full Text Available In the aquaculture industry, feed that is of poor quality or nutritionally imbalanced can cause problems including low weight, poor growth, poor palatability, and increased mortality, all of which can induce a decrease in aquaculture production. Fishmeal is considered a better source of protein and its addition as an ingredient in the aquafeed makes aquatic animals grow fast and healthy. This means that fishmeal is the most important feed ingredient in aquafeed for the aquaculture industry. For the aquaculture industry in Taiwan, about 144,000 ton/USD $203,245,000 of fishmeal was imported, mostly from Peru, in 2016. Therefore, the evaluation and selection of fishmeal suppliers is a very important part of the decision-making process for a Taiwanese aquaculture enterprise. This study constructed a multiple criteria decision-making evaluation model for the selection of fishmeal suppliers using the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR approach based on the weights obtained with the entropy method in a fuzzy decision-making environment. This hybrid approach could effectively and conveniently measure the comprehensive performance of the main Peruvian fishmeal suppliers for practical applications. In addition, the results and processes described herein function as a good reference for an aquaculture enterprise in making decisions when purchasing fishmeal.

  19. A fuzzy approach to the generation expansion planning problem in a multi-objective environment

    International Nuclear Information System (INIS)

    Abass, S. A.; Massoud, E. M. A.; Abass, S. A.)

    2007-01-01

    In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. (author)

  20. A STRUCTURE APPROACH FOR A PHOTOVOLTAIC STATION CONTROL BASED ON ADAPTIVE FUZZY AGENT

    Directory of Open Access Journals (Sweden)

    I. A. Elzein

    2017-01-01

    Full Text Available The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP a complicated problem. To overcome this problem, many maximum power point tracking (MPPT control algorithms have been presented. Fuzzy logic (FL has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in

  1. Application of a collaborative modelling and strategic fuzzy decision support system for selecting appropriate resilience strategies for seaport operations

    Directory of Open Access Journals (Sweden)

    Andrew John

    2014-06-01

    Full Text Available The selection of an appropriate resilience investment strategy to optimize the operational efficiency of a seaport is a challenging task given that many criteria need to be considered and modelled under an uncertain environment. The design of such a complex decision system consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a fuzzy multi-attribute decision making methodology for the selection of an appropriate resilience investment strategy in a succinct and straightforward manner. The decision support model allows for a collaborative modelling of the system by multiple analysts in a group decision making process. Fuzzy analytical hierarchy process (FAHP was utilized to analyse the complex structure of the system to obtain the weights of all the criteria while fuzzy technique for order of preference by similarity to ideal solution (TOPSIS was employed to facilitate the ranking process of the resilience strategies. Given that it is often financially difficult to invest in all the resilience strategies, it is envisaged that the proposed approach could provide decision makers with a flexible and transparent tool for selecting appropriate resilience strategies aimed at increasing the resilience of seaport operations.

  2. a fuzzy logic approach to non-linearity problem of load frequency

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... reduction in settling time, percent overshoot and steady state error. Keywords: fuzzy logic ... power system to regain a state of operating equilibrium given ... power system depends basically on the active (real) power balance ...

  3. A Novel Fuzzy Topological Approach to the Detection of Mammographic Lesions and Quantification of Parenchymal Density

    National Research Council Canada - National Science Library

    Udupa, Jayaram

    2001-01-01

    .... During this project period, the following have been accomplished: The development and validation of a new method of lesion and density detection based on fuzzy connectedness that utilizes the relative strength of connectedness among objects...

  4. Reliable Portfolio Selection Problem in Fuzzy Environment: An mλ Measure Based Approach

    Directory of Open Access Journals (Sweden)

    Yuan Feng

    2017-04-01

    Full Text Available This paper investigates a fuzzy portfolio selection problem with guaranteed reliability, in which the fuzzy variables are used to capture the uncertain returns of different securities. To effectively handle the fuzziness in a mathematical way, a new expected value operator and variance of fuzzy variables are defined based on the m λ measure that is a linear combination of the possibility measure and necessity measure to balance the pessimism and optimism in the decision-making process. To formulate the reliable portfolio selection problem, we particularly adopt the expected total return and standard variance of the total return to evaluate the reliability of the investment strategies, producing three risk-guaranteed reliable portfolio selection models. To solve the proposed models, an effective genetic algorithm is designed to generate the approximate optimal solution to the considered problem. Finally, the numerical examples are given to show the performance of the proposed models and algorithm.

  5. DESIGN OF ROBUST COMMAND TO LINE-OF-SIGHT GUIDANCE LAW: A FUZZY ADAPTIVE APPROACH

    Directory of Open Access Journals (Sweden)

    ESMAIL SADEGHINASAB

    2016-11-01

    Full Text Available In this paper, the design of command to line-of-sight (CLOS missile guidance law is addressed. Taking a three dimensional guidance model, the tracking control problem is formulated. To solve the target tracking problem, the feedback linearization controller is first designed. Although such control scheme possesses the simplicity property, but it presents the acceptable performance only in the absence of perturbations. In order to ensure the robustness properties against model uncertainties, a fuzzy adaptive algorithm is proposed with two parts including a fuzzy (Mamdani system, whose rules are constructed based on missile guidance, and a so-called rule modifier to compensate the fuzzy rules, using the negative gradient method. Compared with some previous works, such control strategy provides a faster time response without large control efforts. The performance of feedback linearization controller is also compared with that of fuzzy adaptive strategy via various simulations.

  6. An approach to decision-making with triangular fuzzy reciprocal preference relations and its application

    Science.gov (United States)

    Meng, Fanyong

    2018-02-01

    Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers' fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.

  7. A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

  8. Fuzzy inference game approach to uncertainty in business decisions and market competitions.

    Science.gov (United States)

    Oderanti, Festus Oluseyi

    2013-01-01

    The increasing challenges and complexity of business environments are making business decisions and operations more difficult for entrepreneurs to predict the outcomes of these processes. Therefore, we developed a decision support scheme that could be used and adapted to various business decision processes. These involve decisions that are made under uncertain situations such as business competition in the market or wage negotiation within a firm. The scheme uses game strategies and fuzzy inference concepts to effectively grasp the variables in these uncertain situations. The games are played between human and fuzzy players. The accuracy of the fuzzy rule base and the game strategies help to mitigate the adverse effects that a business may suffer from these uncertain factors. We also introduced learning which enables the fuzzy player to adapt over time. We tested this scheme in different scenarios and discover that it could be an invaluable tool in the hand of entrepreneurs that are operating under uncertain and competitive business environments.

  9. Fuzzy multi-criteria approach to ordering policy ranking in a supply chain

    Directory of Open Access Journals (Sweden)

    Tadić Danijela

    2005-01-01

    Full Text Available In this paper, a new fuzzy multi-criteria mathematical model for the selection of the best among a finite number of ordering policy of raw material in a supply chain is developed. The problem treated is a part of the purchasing plan of a company in an uncertain environment and it is very common in business practice. Optimization criteria selected describe the performance measures of ordering policies and generally their relative importance is different. It is assumed that the values of the optimization criteria are vague and imprecise. They are described by discrete fuzzy numbers and by linguistic expressions. The linguistic expressions are modeled by discrete fuzzy sets. The measures of belief that one ordering policy is better than another are defined by comparing fuzzy numbers. An illustrative example is given.

  10. Decision making models and human factors: TOPSIS and Ergonomic Behaviors (TOPSIS-EB

    Directory of Open Access Journals (Sweden)

    Mohammad

    2017-02-01

    Full Text Available An effective safety management requires attention to human factors as well as system compo-nents which make risky or safe situations at technical components. This study evaluates and ana-lyze ergonomic behaviors in order to select the best work shift group in an Iranian process in-dustry, in 2010.The methodology was based on the Ergonomic Behavior Sampling (EBS, and TOPSIS method. After specifying the unergonomic behaviors and with reference to the results of a pilot study, a sample of 1755 was determined, with a sampling accuracy of 5% and confi-dence level of 95%. However, in order to gain more confidence, 2631 observations were collect-ed. The results indicate that 43.6% of workers’ behaviors were unergonomic. The most frequent unergonomic behavior was amusing of legs while load lifting with 83.01% of total unergonomic behaviors observations. Using TOPSIS method, the most effective shift group and the least at-tractive alternatives for intervention were selected in this company. Findings declare high number of unergonomic behaviors. Catastrophic consequences of accidents in petrochemical industry ne-cessitate attention to workers’ ergonomic behaviors in the workplace and promotion of them.

  11. Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

    Science.gov (United States)

    Julie, E Golden; Selvi, S Tamil

    2016-01-01

    Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

  12. Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    E. Golden Julie

    2016-01-01

    Full Text Available Wireless sensor networks (WSNs consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

  13. A new approach to self-organizing fuzzy polynomial neural networks guided by genetic optimization

    International Nuclear Information System (INIS)

    Oh, Sung-Kwun; Pedrycz, Witold

    2005-01-01

    In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks (FPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology. The underlying methodology involves mechanisms of genetic optimization, especially genetic algorithms (GAs). Let us recall that the design of the 'conventional' FPNNs uses an extended Group Method of Data Handling (GMDH) and exploits a fixed fuzzy inference type located at each FPN of the FPNN as well as considers a fixed number of input nodes at FPNs (or nodes) located in each layer. The proposed FPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. The structural optimization is realized via GAs whereas in the case of the parametric optimization we proceed with a standard least square method based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. The performance of the proposed gFPNN is quantified through experimentation that exploits standard data already being used in fuzzy modeling. The results reveal superiority of the proposed networks over the existing fuzzy and neural models

  14. Indexing the Environmental Quality Performance Based on A Fuzzy Inference Approach

    Science.gov (United States)

    Iswari, Lizda

    2018-03-01

    Environmental performance strongly deals with the quality of human life. In Indonesia, this performance is quantified through Environmental Quality Index (EQI) which consists of three indicators, i.e. river quality index, air quality index, and coverage of land cover. The current of this instrument data processing was done by averaging and weighting each index to represent the EQI at the provincial level. However, we found EQI interpretations that may contain some uncertainties and have a range of circumstances possibly less appropriate if processed under a common statistical approach. In this research, we aim to manage the indicators of EQI with a more intuitive computation technique and make some inferences related to the environmental performance in 33 provinces in Indonesia. Research was conducted in three stages of Mamdani Fuzzy Inference System (MAFIS), i.e. fuzzification, data inference, and defuzzification. Data input consists of 10 environmental parameters and the output is an index of Environmental Quality Performance (EQP). Research was applied to the environmental condition data set in 2015 and quantified the results into the scale of 0 to 100, i.e. 10 provinces at good performance with the EQP above 80 dominated by provinces in eastern part of Indonesia, 22 provinces with the EQP between 80 to 50, and one province in Java Island with the EQP below 20. This research shows that environmental quality performance can be quantified without eliminating the natures of the data set and simultaneously is able to show the environment behavior along with its spatial pattern distribution.

  15. Cooperative Fuzzy Games Approach to Setting Target Levels of ECs in Quality Function Deployment

    Directory of Open Access Journals (Sweden)

    Zhihui Yang

    2014-01-01

    Full Text Available Quality function deployment (QFD can provide a means of translating customer requirements (CRs into engineering characteristics (ECs for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.

  16. An Ontological-Fuzzy Approach to Advance Reservation in Multi-Cluster Grids

    International Nuclear Information System (INIS)

    Ferreira, D J; Dantas, M A R; Bauer, Michael A

    2010-01-01

    Advance reservation is an important mechanism for a successful utilization of available resources in distributed multi-cluster environments. This mechanism allows, for example, a user to provide parameters aiming to satisfy requirements related to applications' execution time and temporal dependence. This predictability can lead the system to reach higher levels of QoS. However, the support for advance reservation has been restricted due to the complexity of large scale configurations and also dynamic changes verified in these systems. In this research work it is proposed an advance reservation method, based on a ontology-fuzzy approach. It allows a user to reserve a wide variety of resources and enable large jobs to be reserved among different nodes. In addition, it dynamically verifies the possibility of reservation with the local RMS, avoiding future allocation conflicts. Experimental results of the proposal, through simulation, indicate that the proposed mechanism reached a successful level of flexibility for large jobs and more appropriated distribution of resources in a distributed multi-cluster configuration.

  17. Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system

    International Nuclear Information System (INIS)

    Sabahi, Kamel; Teshnehlab, Mohammad; Shoorhedeli, Mahdi Aliyari

    2009-01-01

    In this study, a new adaptive controller based on modified feedback error learning (FEL) approaches is proposed for load frequency control (LFC) problem. The FEL strategy consists of intelligent and conventional controllers in feedforward and feedback paths, respectively. In this strategy, a conventional feedback controller (CFC), i.e. proportional, integral and derivative (PID) controller, is essential to guarantee global asymptotic stability of the overall system; and an intelligent feedforward controller (INFC) is adopted to learn the inverse of the controlled system. Therefore, when the INFC learns the inverse of controlled system, the tracking of reference signal is done properly. Generally, the CFC is designed at nominal operating conditions of the system and, therefore, fails to provide the best control performance as well as global stability over a wide range of changes in the operating conditions of the system. So, in this study a supervised controller (SC), a lookup table based controller, is addressed for tuning of the CFC. During abrupt changes of the power system parameters, the SC adjusts the PID parameters according to these operating conditions. Moreover, for improving the performance of overall system, a recurrent fuzzy neural network (RFNN) is adopted in INFC instead of the conventional neural network, which was used in past studies. The proposed FEL controller has been compared with the conventional feedback error learning controller (CFEL) and the PID controller through some performance indices

  18. Risk Assessment of Wastewater Collection Performance Using the Fuzzy Decision-making Approach

    Directory of Open Access Journals (Sweden)

    Maedeh Asgarian

    2015-10-01

    Full Text Available Wastewater collection network simulation in normal conditions dose not provide performance assessment in unusual circumstances. In this paper, a model has been developed for risk assessment of wastewater collection systems to manage their performance under natural or man-made critical conditions. In this model, certain criteria were defined, fuzzy MADM techniques were exploited, and a questionnaire was employed to measure such risk parameters as the probability of threats, the severity of their impacts, and the vulnerability of the network components. Based on the calculated magnitude of the risks, the threats and hazards were classified into groups ranging from low-risk to high-risk threats. The approaches adopted to combat the risks were also classified into the following three categories: "to deal with the risk", "risk shifting", and "risk taking". This process was implemented for the wastewater collection system in Shahrak-Gharb District in Tehran as a case study. ‘Introduction of chemical pollutants into the sewers’ and ‘drastic changes in wastewater quality’ were identified as the most threatening crises for the district and the ‘risk reduction strategy’ was proposed for combating the critical conditions in this district.

  19. An Ontological-Fuzzy Approach to Advance Reservation in Multi-Cluster Grids

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, D J; Dantas, M A R; Bauer, Michael A, E-mail: ded@inf.ufsc.br, E-mail: mario@inf.ufsc.br, E-mail: bauer@csd.uwo.ca

    2010-11-01

    Advance reservation is an important mechanism for a successful utilization of available resources in distributed multi-cluster environments. This mechanism allows, for example, a user to provide parameters aiming to satisfy requirements related to applications' execution time and temporal dependence. This predictability can lead the system to reach higher levels of QoS. However, the support for advance reservation has been restricted due to the complexity of large scale configurations and also dynamic changes verified in these systems. In this research work it is proposed an advance reservation method, based on a ontology-fuzzy approach. It allows a user to reserve a wide variety of resources and enable large jobs to be reserved among different nodes. In addition, it dynamically verifies the possibility of reservation with the local RMS, avoiding future allocation conflicts. Experimental results of the proposal, through simulation, indicate that the proposed mechanism reached a successful level of flexibility for large jobs and more appropriated distribution of resources in a distributed multi-cluster configuration.

  20. A Fuzzy Color-Based Approach for Understanding Animated Movies Content in the Indexing Task

    Directory of Open Access Journals (Sweden)

    Vasile Buzuloiu

    2008-04-01

    Full Text Available This paper proposes a method for detecting and analyzing the color techniques used in the animated movies. Each animated movie uses a specific color palette which makes its color distribution one major feature in analyzing the movie content. The color palette is specially tuned by the author in order to convey certain feelings or to express artistic concepts. Deriving semantic or symbolic information from the color concepts or the visual impression induced by the movie should be an ideal way of accessing its content in a content-based retrieval system. The proposed approach is carried out in two steps. The first processing step is the low-level analysis. The movie color content gets represented with several global statistical parameters computed from the movie global weighted color histogram. The second step is the symbolic representation of the movie content. The numerical parameters obtained from the first step are converted into meaningful linguistic concepts through a fuzzy system. They concern mainly the predominant hues of the movie, some of Itten’s color contrasts and harmony schemes, color relationships and color richness. We use the proposed linguistic concepts to link to given animated movies according to their color techniques. In order to make the retrieval task easier, we also propose to represent color properties in a graphical manner which is similar to the color gamut representation. Several tests have been conducted on an animated movie database.

  1. An iterative method for tri-level quadratic fractional programming problems using fuzzy goal programming approach

    Science.gov (United States)

    Kassa, Semu Mitiku; Tsegay, Teklay Hailay

    2017-08-01

    Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.

  2. Power Consumption Reduction for Wireless Sensor Networks Using A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Giovanni Pau

    2016-01-01

    Full Text Available The increasing complexity of Wireless Sensor Networks (WSNs is leading towards the deployment of complex networked systems and the optimal design of WSNs can be a very difficult task because several constraints and requirements must be considered, among all the power consumption. This paper proposes a novel fuzzy logic based mechanism that according to the battery level and to the ratio of Throughput to Workload determines the sleeping time of sensor devices in a Wireless Sensor Network for environmental monitoring based on the IEEE 802.15.4 protocol. The main aim here is to find an effective solution that achieves the target while avoiding complex and computationally expensive solutions, which would not be appropriate for the problem at hand and would impair the practical applicability of the approach in real scenarios. The results of several real test-bed scenarios show that the proposed system outperforms other solutions, significantly reducing the whole power consumption while maintaining good performance in terms of the ratio of throughput to workload. An implementation on off-the-shelf devices proves that the proposed controller does not require powerful hardware and can be easily implemented on a low-cost device, thus paving the way for extensive usage in practice.

  3. Cooperative fuzzy games approach to setting target levels of ECs in quality function deployment.

    Science.gov (United States)

    Yang, Zhihui; Chen, Yizeng; Yin, Yunqiang

    2014-01-01

    Quality function deployment (QFD) can provide a means of translating customer requirements (CRs) into engineering characteristics (ECs) for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.

  4. A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

    Directory of Open Access Journals (Sweden)

    Rafael de Carvalho Miranda

    2014-01-01

    Full Text Available The development of discrete-event simulation software was one of the most successful interfaces in operational research with computation. As a result, research has been focused on the development of new methods and algorithms with the purpose of increasing simulation optimization efficiency and reliability. This study aims to define optimum variation intervals for each decision variable through a proposed approach which combines the data envelopment analysis with the Fuzzy logic (Fuzzy-DEA-BCC, seeking to improve the decision-making units’ distinction in the face of uncertainty. In this study, Taguchi’s orthogonal arrays were used to generate the necessary quantity of DMUs, and the output variables were generated by the simulation. Two study objects were utilized as examples of mono- and multiobjective problems. Results confirmed the reliability and applicability of the proposed method, as it enabled a significant reduction in search space and computational demand when compared to conventional simulation optimization techniques.

  5. Evaluation model of project complexity for large-scale construction projects in Iran - A Fuzzy ANP approach

    Directory of Open Access Journals (Sweden)

    Aliyeh Kazemi

    2016-09-01

    Full Text Available Construction projects have always been complex. By growing trend of this complexity, implementations of large-scale constructions become harder. Hence, evaluating and understanding these complexities are critical. Correct evaluation of a project complication can provide executives and managers with good source to use. Fuzzy analytic network process (ANP is a logical and systematic approach toward defining, evaluation, and grading. This method allows for analyzing complex systems, and determining complexity of them. In this study, by taking advantage of fuzzy ANP, effective indexes for development of complications in large-scale construction projects in Iran have been determined and prioritized. The results show socio-political, project system interdependencies, and technological complexity indexes ranked top to three. Furthermore, in comparison of three main huge projects: commercial-administrative, hospital, and skyscrapers, the hospital project had been evaluated as the most complicated. This model is beneficial for professionals in managing large-scale projects.

  6. Design of polynomial fuzzy observer-controller for nonlinear systems with state delay: sum of squares approach

    Science.gov (United States)

    Gassara, H.; El Hajjaji, A.; Chaabane, M.

    2017-07-01

    This paper investigates the problem of observer-based control for two classes of polynomial fuzzy systems with time-varying delay. The first class concerns a special case where the polynomial matrices do not depend on the estimated state variables. The second one is the general case where the polynomial matrices could depend on unmeasurable system states that will be estimated. For the last case, two design procedures are proposed. The first one gives the polynomial fuzzy controller and observer gains in two steps. In the second procedure, the designed gains are obtained using a single-step approach to overcome the drawback of a two-step procedure. The obtained conditions are presented in terms of sum of squares (SOS) which can be solved via the SOSTOOLS and a semi-definite program solver. Illustrative examples show the validity and applicability of the proposed results.

  7. Application of Generalized Hukuhara derivative approach in an economic production quantity model with partial trade credit policy under fuzzy environment

    Directory of Open Access Journals (Sweden)

    Pinki Majumder

    2016-01-01

    Full Text Available In this present study, a production inventory model with partial trade credit is formulated and solved in fuzzy environment via Generalized Hukuhara derivative approach. To capture the market, a supplier offers a trade credit period to its retailers. Due to this facility, retailer also offers a partial trade credit period to his/her customer to boost the demand of the item. In practical life situation, demands are generally dependent upon time. Constant demand of an item varies time to time. In this vague situation, demands are taken as time dependent, where its constant part is taken as Left Right - type fuzzy number. In this paper, Generalized Hukuhara derivative approach is used to solve the fuzzy inventory model. Four different cases are considered by using Generalized Hukuhara-(i differentiability and Generalized Hukuhara-(ii differentiability. The objective of this paper is to find out the optimal time so as the total inventory cost is minimum. Finally the model is solved by generalized reduced gradient method. The proposed model and technique are illustrated by numerical examples. Some sensitivity analyses both in tabular and graphical forms are presented and the effects of minimum cost with respect to various inventory parameters are discussed.

  8. Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

    Science.gov (United States)

    Subagadis, Y. H.; Schütze, N.; Grundmann, J.

    2014-09-01

    The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

  9. Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

    Directory of Open Access Journals (Sweden)

    Y. H. Subagadis

    2014-09-01

    Full Text Available The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water–society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

  10. Real-Time Fault Detection Approach for Nonlinear Systems and its Asynchronous T-S Fuzzy Observer-Based Implementation.

    Science.gov (United States)

    Li, Linlin; Ding, Steven X; Qiu, Jianbin; Yang, Ying

    2017-02-01

    This paper is concerned with a real-time observer-based fault detection (FD) approach for a general type of nonlinear systems in the presence of external disturbances. To this end, in the first part of this paper, we deal with the definition and the design condition for an L ∞ / L 2 type of nonlinear observer-based FD systems. This analytical framework is fundamental for the development of real-time nonlinear FD systems with the aid of some well-established techniques. In the second part, we address the integrated design of the L ∞ / L 2 observer-based FD systems by applying Takagi-Sugeno (T-S) fuzzy dynamic modeling technique as the solution tool. This fuzzy observer-based FD approach is developed via piecewise Lyapunov functions, and can be applied to the case that the premise variables of the FD system is nonsynchronous with the premise variables of the fuzzy model of the plant. In the end, a case study on the laboratory setup of three-tank system is given to show the efficiency of the proposed results.

  11. Ranking factors involved in product design using a hybrid model of Quality Function Deployment, Data Envelopment Analysis and TOPSIS technique

    Directory of Open Access Journals (Sweden)

    Davood Feiz

    2014-08-01

    Full Text Available Quality function deployment (QFD is one such extremely important quality management tool, which is useful in product design and development. Traditionally, QFD rates the design requirements (DRs with respect to customer requirements, and aggregates the rating to get relative importance score of DRs. An increasing number of studies emphasize on the need to incorporate additional factors, such as cost and environmental impact, while calculating the relative importance of DRs. However, there are different methodologies for driving the relative importance of DRs, when several additional factors are considered. TOPSIS (technique for order preferences by similarity to ideal solution is suggested for the purpose of the research. This research proposes new approach of TOPSIS for considering the rating of DRs with respect to CRs, and several additional factors, simultaneously. Proposed method is illustrated using by step-by-step procedure. The proposed methodology was applied for the Sanam Electronic Company in Iran.

  12. An Object-Oriented Approach of Keyword Querying over Fuzzy XML

    Directory of Open Access Journals (Sweden)

    Ting Li

    2016-09-01

    Full Text Available As the fuzzy data management has become one of the main research topics and directions, the question of how to obtain the useful information by means of keyword query from fuzzy XML documents is becoming a subject of an increasing needed investigation. Considering the keyword query methods on crisp XML documents, smallest lowest common ancestor (SLCA semantics is one of the most widely accepted semantics. When users propose the keyword query on fuzzy XML documents with the SLCA semantics, the query results are always incomplate, with low precision, and with no possibilities values returned. Most of keyword query semantics on XML documents only consider query results matching all keywords, yet users may also be interested in the query results matching partial keywords. To overcome these limitations, in this paper, we investigate how to obtain more comprehensive and meaningful results of keyword querying on fuzzy XML documents. We propose a semantics of object-oriented keyword querying on fuzzy XML documents. First, we introduce the concept of "object tree", analyze different types of matching result object trees and find the "minimum result object trees" which contain all keywords and "result object trees" which contain partial keywords. Then an object-oriented keyword query algorithm ROstack is proposed to obtain the root nodes of these matching result object trees, together with their possibilities. At last, experiments are conducted to verify the effectiveness and efficiency of our proposed algorithm.

  13. A new approach to the statistical treatment of 2D-maps in proteomics using fuzzy logic.

    Science.gov (United States)

    Marengo, Emilio; Robotti, Elisa; Gianotti, Valentina; Righetti, Pier Giorgio

    2003-01-01

    A new approach to the statistical treatment of 2D-maps has been developed. This method is based on the use of fuzzy logic and allows to take into consideration the typical low reproducibility of 2D-maps. In this approach the signal corresponding to the presence of proteins on the 2D-maps is substituted with probability functions, centred on the signal itself. The standard deviation of the bidimensional gaussian probability function employed to blur the signal allows to assign different uncertainties to the two electrophoretic dimensions. The effect of changing the standard deviation and the digitalisation resolution are investigated.

  14. Knapsack--TOPSIS Technique for Vertical Handover in Heterogeneous Wireless Network.

    Directory of Open Access Journals (Sweden)

    E M Malathy

    Full Text Available In a heterogeneous wireless network, handover techniques are designed to facilitate anywhere/anytime service continuity for mobile users. Consistent best-possible access to a network with widely varying network characteristics requires seamless mobility management techniques. Hence, the vertical handover process imposes important technical challenges. Handover decisions are triggered for continuous connectivity of mobile terminals. However, bad network selection and overload conditions in the chosen network can cause fallout in the form of handover failure. In order to maintain the required Quality of Service during the handover process, decision algorithms should incorporate intelligent techniques. In this paper, a new and efficient vertical handover mechanism is implemented using a dynamic programming method from the operation research discipline. This dynamic programming approach, which is integrated with the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS method, provides the mobile user with the best handover decisions. Moreover, in this proposed handover algorithm a deterministic approach which divides the network into zones is incorporated into the network server in order to derive an optimal solution. The study revealed that this method is found to achieve better performance and QoS support to users and greatly reduce the handover failures when compared to the traditional TOPSIS method. The decision arrived at the zone gateway using this operational research analytical method (known as the dynamic programming knapsack approach together with Technique to Order Preference by Similarity to Ideal Solution yields remarkably better results in terms of the network performance measures such as throughput and delay.

  15. A decision making method based on interval type-2 fuzzy sets: An approach for ambulance location preference

    Directory of Open Access Journals (Sweden)

    Lazim Abdullah

    2018-01-01

    Full Text Available Selecting the best solution to deploy an ambulance in a strategic location is of the important variables that need to be accounted for improving the emergency medical services. The selection requires both quantitative and qualitative evaluation. Fuzzy set based approach is one of the well-known theories that help decision makers to handle fuzziness, uncertainty in decision making and vagueness of information. This paper proposes a new decision making method of Interval Type-2 Fuzzy Simple Additive Weighting (IT2 FSAW as to deal with uncertainty and vagueness. The new IT2 FSAW is applied to establish a preference in ambulance location. The decision making framework defines four criteria and five alternatives of ambulance location preference. Four experts attached to a Malaysian government hospital and a university medical center were interviewed to provide linguistic evaluation prior to analyzing with the new IT2 FSAW. Implementation of the proposed method in the case of ambulance location preference suggests that the ‘road network’ is the best alternative for ambulance location. The results indicate that the proposed method offers a consensus solution for handling the vague and qualitative criteria of ambulance location preference.

  16. Optimization of Urban Highway Bypass Horizontal Alignment: A Methodological Overview of Intelligent Spatial MCDA Approach Using Fuzzy AHP and GIS

    Directory of Open Access Journals (Sweden)

    Yashon O. Ouma

    2014-01-01

    Full Text Available Selection of urban bypass highway alternatives involves the consideration of competing and conflicting criteria and factors, which require multicriteria decision analysis. Analytic hierarchy process (AHP is one of the most commonly used multicriteria decision making (MCDM methods that can integrate personal preferences in performing spatial analyses on the physical and nonphysical parameters. In this paper, the traditional AHP is modified to fuzzy AHP for the determination of the optimal bypass route for Eldoret town in Kenya. The fuzzy AHP is proposed in order to take care of the vagueness type uncertainty encountered in alternative bypass location determination. In the implementation, both engineering and environmental factors comprising of physical and socioeconomic objectives were considered at different levels of decision hierarchy. The results showed that the physical objectives (elevation, slope, soils, geology, and drainage networks and socioeconomic objectives (land-use and road networks contributed the same weight of 0.5 towards the bypass location prioritization process. At the subcriteria evaluation level, land-use and existing road networks contributed the highest significance of 47.3% amongst the seven decision factors. Integrated with GIS-based least cost path (LCP analysis, the fuzzy AHP results produced the most desirable and optimal route alignment, as compared to the AHP only prioritization approach.

  17. Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans

    Science.gov (United States)

    Si, Guangsen; Xu, Zeshui

    2018-01-01

    Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method. PMID:29614019

  18. Ranking the strategies for Indian medical tourism sector through the integration of SWOT analysis and TOPSIS method.

    Science.gov (United States)

    Ajmera, Puneeta

    2017-10-09

    Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.

  19. Nuclear reactor control with fuzzy logic approaches - strengths, weakness, opportunities, and threats

    International Nuclear Information System (INIS)

    Ruan, Da

    2004-01-01

    As part of the special track on 'Lessons learned from computational intelligence in nuclear applications' at the forthcoming FLINS 2004 conference on Applied Computational Intelligence (Blankenberge, Belgium, September 1-3, 2004), research experiences on fuzzy logic techniques in applications of nuclear reactor control operation are critically reviewed in this presentation. Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined thought a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK-CEN) and the Mexican Nuclear Centre (ININ) on the fuzzy logic control for nuclear reactor control project under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (Author)

  20. Automatic generation control of TCPS based hydrothermal system under open market scenario: A fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Rao, C. Srinivasa [EEE Department, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh (India); Nagaraju, S. Siva [EEE Department, J.N.T.U College of Engg., Kakinada, Andhra Pradesh (India); Raju, P. Sangameswara [EEE Department, S.V. University, Tirupati, Andhra Pradesh (India)

    2009-09-15

    This paper presents the analysis of automatic generation control of a two-area interconnected thyristor controlled phase shifter based hydrothermal system in the continuous mode using fuzzy logic controller under open market scenario. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of AGC problem. So the traditional AGC two-area system is modified to take into account the effect of bilateral contracts on the dynamics. It is possible to stabilize the system frequency and tie-power oscillations by controlling the phase angle of TCPS which is expected to provide a new ancillary service for the future power systems. A control strategy using TCPS is proposed to provide active control of system frequency. Further dynamic responses for small perturbation considering fuzzy logic controller and PI controller (dual mode controller) have been observed and the superior performance of fuzzy logic controller has been reported analytically and also through simulation. (author)

  1. The foundations of fuzzy control

    CERN Document Server

    Lewis, Harold W

    1997-01-01

    Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

  2. Optimal layout of radiological environment monitoring based on TOPSIS method

    International Nuclear Information System (INIS)

    Li Sufen; Zhou Chunlin

    2006-01-01

    TOPSIS is a method for multi-objective-decision-making, which can be applied to comprehensive assessment of environmental quality. This paper adopts it to get the optimal layout of radiological environment monitoring, it is proved that this method is a correct, simple and convenient, practical one, and beneficial to supervision departments to scientifically and reasonably layout Radiological Environment monitoring sites. (authors)

  3. Sistem Pendukung Keputusan Untuk Pengadaan Fasilitas Hotel Menggunakan Metode TOPSIS

    Directory of Open Access Journals (Sweden)

    Susi Hendartie

    2014-01-01

    Full Text Available The development of hotel business to make consumers more critical to choose a hotel products and services. If the hotel facilities more complete, so interest of the consumer is higher to choose the hotel. This  research study intend to build a decision support system for the procurement of hotel facilities with TOPSIS method. This method uses the six alternative form of the data; hotel rooms (guest  room, karaoke, gift shop, a gym, spa and travel corner (travel tour information and data of some criteria. This method was chosen because it is based on the best alternative concept, was not only has the shortest distance from the positive ideal solution, but also has  the longest distance  from  the  negative  ideal  solution.  TOPSIS  calculations  systems  have  been  done  the  comparison  of  final  value  using  excell calculation. Calculations that used in this research study is simple and produces alternative hotel rooms (guest room with t he highest ranking as the ideal solution. TOPSIS method facilitates decision-makers in choosing the best alternative for the procurement of hotel facilities.Keywords : Decision support system; Hotel facilities; TOPSIS

  4. QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

    Directory of Open Access Journals (Sweden)

    Jaeho Cho

    2015-01-01

    Full Text Available Users’ satisfaction on quality is a key that leads successful completion of the project in relation to decision-making issues in building design solutions. This study proposed QFD (quality function deployment based benchmarking logic of market products for building envelope solutions. Benchmarking logic is composed of QFD-TOPSIS and QFD-SI. QFD-TOPSIS assessment model is able to evaluate users’ preferences on building envelope solutions that are distributed in the market and may allow quick achievement of knowledge. TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution provides performance improvement criteria that help defining users’ target performance criteria. SI (Suitability Index allows analysis on suitability of the building envelope solution based on users’ required performance criteria. In Stage 1 of the case study, QFD-TOPSIS was used to benchmark the performance criteria of market envelope products. In Stage 2, a QFD-SI assessment was performed after setting user performance targets. The results of this study contribute to confirming the feasibility of QFD based benchmarking in the field of Building Envelope Performance Assessment (BEPA.

  5. Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

    Science.gov (United States)

    Zaiwani, B. E.; Zarlis, M.; Efendi, S.

    2018-03-01

    In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

  6. Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage.

    Science.gov (United States)

    Zhang, Limao; Wu, Xianguo; Qin, Yawei; Skibniewski, Miroslaw J; Liu, Wenli

    2016-02-01

    Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel-induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step-by-step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN-based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel-induced pipeline damage model is proposed to reveal the cause-effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment. © 2015 Society for Risk Analysis.

  7. Water supply management using an extended group fuzzy decision-making method: a case study in north-eastern Iran

    Science.gov (United States)

    Minatour, Yasser; Bonakdari, Hossein; Zarghami, Mahdi; Bakhshi, Maryam Ali

    2015-09-01

    The purpose of this study was to develop a group fuzzy multi-criteria decision-making method to be applied in rating problems associated with water resources management. Thus, here Chen's group fuzzy TOPSIS method extended by a difference technique to handle uncertainties of applying a group decision making. Then, the extended group fuzzy TOPSIS method combined with a consistency check. In the presented method, initially linguistic judgments are being surveyed via a consistency checking process, and afterward these judgments are being used in the extended Chen's fuzzy TOPSIS method. Here, each expert's opinion is turned to accurate mathematical numbers and, then, to apply uncertainties, the opinions of group are turned to fuzzy numbers using three mathematical operators. The proposed method is applied to select the optimal strategy for the rural water supply of Nohoor village in north-eastern Iran, as a case study and illustrated example. Sensitivity analyses test over results and comparing results with project reality showed that proposed method offered good results for water resources projects.

  8. A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations

    Directory of Open Access Journals (Sweden)

    Jun-Lin Lin

    2014-01-01

    Full Text Available A system of fuzzy relational equations with the max-Archimedean t-norm composition was considered. The relevant literature indicated that this problem can be reduced to the problem of finding all the irredundant coverings of a binary matrix. A divide-and-conquer approach is proposed to solve this problem and, subsequently, to solve the original problem. This approach was used to analyze the binary matrix and then decompose the matrix into several submatrices such that the irredundant coverings of the original matrix could be constructed using the irredundant coverings of each of these submatrices. This step was performed recursively for each of these submatrices to obtain the irredundant coverings. Finally, once all the irredundant coverings of the original matrix were found, they were easily converted into the minimal solutions of the fuzzy relational equations. Experiments on binary matrices, with the number of irredundant coverings ranging from 24 to 9680, were also performed. The results indicated that, for test matrices that could initially be partitioned into more than one submatrix, this approach reduced the execution time by more than three orders of magnitude. For the other test matrices, this approach was still useful because certain submatrices could be partitioned into more than one submatrix.

  9. Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

    Science.gov (United States)

    Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

    2017-08-01

    Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

  10. A fuzzy MCDM approach for evaluating school performance based on linguistic information

    Science.gov (United States)

    Musani, Suhaina; Jemain, Abdul Aziz

    2013-11-01

    Decision making is the process of finding the best option among the feasible alternatives. This process should consider a variety of criteria, but this study only focus on academic achievement. The data used is the percentage of candidates who obtained Malaysian Certificate of Education (SPM) in Melaka based on school academic achievement for each subject. 57 secondary schools in Melaka as listed by the Ministry of Education involved in this study. Therefore the school ranking can be done using MCDM (Multi Criteria Decision Making) methods. The objective of this study is to develop a rational method for evaluating school performance based on linguistic information. Since the information or level of academic achievement provided in linguistic manner, there is a possible chance of getting incomplete or uncertain problems. So in order to overcome the situation, the information could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this research, VIKOR (Multi Criteria Optimization and Compromise Solution) has been used as a MCDM tool for the school ranking process in fuzzy environment. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

  11. Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

    Directory of Open Access Journals (Sweden)

    Han Songshan

    2015-02-01

    Full Text Available A fuzzy robust nonlinear controller for hydraulic rotary actuators in flight motion simulators is proposed. Compared with other three-order models of hydraulic rotary actuators, the proposed controller based on first-order nonlinear model is more easily applied in practice, whose control law is relatively simple. It not only does not need high-order derivative of desired command, but also does not require the feedback signals of velocity, acceleration and jerk of hydraulic rotary actuators. Another advantage is that it does not rely on any information of friction, inertia force and external disturbing force/torque, which are always difficult to resolve in flight motion simulators. Due to the special composite vane seals of rectangular cross-section and goalpost shape used in hydraulic rotary actuators, the leakage model is more complicated than that of traditional linear hydraulic cylinders. Adaptive multi-input single-output (MISO fuzzy compensators are introduced to estimate nonlinear uncertain functions about leakage and bulk modulus. Meanwhile, the decomposition of the uncertainties is used to reduce the total number of fuzzy rules. Different from other adaptive fuzzy compensators, a discontinuous projection mapping is employed to guarantee the estimation process to be bounded. Furthermore, with a sufficient number of fuzzy rules, the controller theoretically can guarantee asymptotic tracking performance in the presence of the above uncertainties, which is very important for high-accuracy tracking control of flight motion simulators. Comparative experimental results demonstrate the effectiveness of the proposed algorithm, which can guarantee transient performance and better final accurate tracking in the presence of uncertain nonlinearities and parametric uncertainties.

  12. Application of improved topsis method to comprehensive assessment of radiological environmental quality

    International Nuclear Information System (INIS)

    Shi Dongsheng; Di Yuming; Zhou Chunlin

    2007-01-01

    TOPSIS is a method for multiobjective decision-making, which can be applied to comprehensive assessment of radiological environmental quality. This paper introduces the principle of TOPSIS method and sets up the model of improved TOPSIS method, discusses the application of improved TOPSIS method to comprehensive assessment of radiological environmental quality. This method sufficiently makes use of the information of the optimal matrix. Analysis of practical examples using MATLAB program shows that it is objectively reasonable and feasible to comprehensively assess radiological environmental quality by improved TOPSIS method. This paper also provides the result of optimum number of sites and compares it with optimal index method based on TOPSIS method and traditional method. (authors)

  13. A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry

    2014-01-01

    Highlights: • We propose a fuzzy-based reliability approach to evaluate basic event reliabilities. • It implements the concepts of failure possibilities and fuzzy sets. • Experts evaluate basic event failure possibilities using qualitative words. • Triangular fuzzy numbers mathematically represent qualitative failure possibilities. • It is a very good alternative for conventional reliability approach. - Abstract: Fault tree analysis has been widely utilized as a tool for nuclear power plant probabilistic safety assessment. This analysis can be completed only if all basic events of the system fault tree have their quantitative failure rates or failure probabilities. However, it is difficult to obtain those failure data due to insufficient data, environment changing or new components. This study proposes a fuzzy-based reliability approach to evaluate basic events of system fault trees whose failure precise probability distributions of their lifetime to failures are not available. It applies the concept of failure possibilities to qualitatively evaluate basic events and the concept of fuzzy sets to quantitatively represent the corresponding failure possibilities. To demonstrate the feasibility and the effectiveness of the proposed approach, the actual basic event failure probabilities collected from the operational experiences of the David–Besse design of the Babcock and Wilcox reactor protection system fault tree are used to benchmark the failure probabilities generated by the proposed approach. The results confirm that the proposed fuzzy-based reliability approach arises as a suitable alternative for the conventional probabilistic reliability approach when basic events do not have the corresponding quantitative historical failure data for determining their reliability characteristics. Hence, it overcomes the limitation of the conventional fault tree analysis for nuclear power plant probabilistic safety assessment

  14. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Fuzzy difference and data primitives: a transparent approach for supporting different definitions of forest in the context of REDD+

    Directory of Open Access Journals (Sweden)

    A. Comber

    2018-04-01

    Full Text Available This paper explores the use of fuzzy difference methods in order to understand the differences between forest classes. The context for this work is provided by REDD+, which seeks to reduce the net emissions of greenhouse gases by rewarding the conservation of forests in developing countries. REDD+ requires that local inventories of forest are undertaken and payments are made on the basis of the amount of forest (and associated carbon storage. At the most basic level this involves classifying land into forest and non-forest. However, the critical issues affecting the uptake, buy-in and ultimately the success of REDD+ are the lack of universally agreed definition of forest to support REDD+ mapping activities, and where such a definition is imposed, the marginalization of local community voices and local landscape conceptualizations. This tension is at the heart of REDD+. This paper addresses these issues by linking methods to quantify changes in fuzzy land cover to the concept of data primitives, which have been previously proposed as a suitable approach to move between land cover classes with different semantics. These are applied to case study that quantifies the difference in areas for two definitions of forest derived from the GLC and FAO definitions of forest. The results show how data primitives allow divergent concepts of forest to be represented and mapped from the same data and how the fuzzy sets approach can be used to quantify the differences and non-intersections of different concepts of forest. Together these methods provide for transparent translations between alternative conceptualizations of forest, allowing for plural notions of forest to be mapped and quantified. In particular, they allow for moving from an object-based notion of forest (and land cover in general to a field-based one, entirely avoiding the need for forest boundaries.

  16. Random Fuzzy Extension of the Universal Generating Function Approach for the Reliability Assessment of Multi-State Systems Under Aleatory and Epistemic Uncertainties

    DEFF Research Database (Denmark)

    Li, Yan-Fu; Ding, Yi; Zio, Enrico

    2014-01-01

    . In this work, we extend the traditional universal generating function (UGF) approach for multi-state system (MSS) availability and reliability assessment to account for both aleatory and epistemic uncertainties. First, a theoretical extension, named hybrid UGF (HUGF), is made to introduce the use of random...... fuzzy variables (RFVs) in the approach. Second, the composition operator of HUGF is defined by considering simultaneously the probabilistic convolution and the fuzzy extension principle. Finally, an efficient algorithm is designed to extract probability boxes ($p$ -boxes) from the system HUGF, which...

  17. Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach

    Science.gov (United States)

    Nasiri, Alireza; Nguang, Sing Kiong; Swain, Akshya; Almakhles, Dhafer

    2018-02-01

    This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.

  18. Granular, soft and fuzzy approaches for intelligent systems dedicated to professor Ronald R. Yager

    CERN Document Server

    Filev, Dimitar; Beliakov, Gleb

    2017-01-01

    This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communit...

  19. Fuzzy Quantitive Strategic Planning Matrix dalam Perencanaan Strategi Perguruan Tinggi

    Directory of Open Access Journals (Sweden)

    Fera Tri Wulandari

    2016-01-01

    Full Text Available The strategic plan helps the college in determining the direction of the college to achieve a desired future and provides a framework for achieving competitive advantage. In the strategic planning process, the selection of strategies is essential if universities do not have the resources to implement all the strategies. FQSPM designed to determine the relative attractiveness of each alternative strategy using triangular fuzzy numbers. Merger FQSPM and FTOPSIS used in the decision-making process on strategic planning by a college to conduct the election strategy based on the results of internal and external analysis. The results of the strategic planning helps colleges determine the direction to achieve the desired future so that colleges can anticipate environmental changes and predict the risk while continuing to adjust the action with the aim to be achieved college. Keywords: Strategic Planning; SWOT; Fuzzy QSPM; Fuzzy TOPSIS

  20. Fractional variational problems and particle in cell gyrokinetic simulations with fuzzy logic approach for tokamaks

    Directory of Open Access Journals (Sweden)

    Rastović Danilo

    2009-01-01

    Full Text Available In earlier Rastovic's papers [1] and [2], the effort was given to analyze the stochastic control of tokamaks. In this paper, the deterministic control of tokamak turbulence is investigated via fractional variational calculus, particle in cell simulations, and fuzzy logic methods. Fractional integrals can be considered as approximations of integrals on fractals. The turbulent media could be of the fractal structure and the corresponding equations should be changed to include the fractal features of the media.

  1. A Fuzzy-Grey Multicriteria Decision Making Approach for Green Supplier Selection in Low-Carbon Supply Chain

    Directory of Open Access Journals (Sweden)

    Qinghua Pang

    2017-01-01

    Full Text Available Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.

  2. Applying a neuro-fuzzy approach for transient identification in a nuclear power plant

    International Nuclear Information System (INIS)

    Costa, Rafael G.; Mol, Antonio C.A.; Pereira, Claudio M.N.A.; Carvalho, Paulo V.R.

    2009-01-01

    Transient identification in Nuclear Power Plant (NPP) is often a very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Several systems based on specialist systems, neural networks, and fuzzy logic have been developed for transient identification. In the work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A preliminary evaluation of the developed system was made at the Human-System Interface Laboratory (LABIHS). The obtained results show that the system can help the operators to take decisions during transients/accidents in the plant. (author)

  3. Fuzzy logic

    CERN Document Server

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  4. Fuzzy Languages

    Science.gov (United States)

    Rahonis, George

    The theory of fuzzy recognizable languages over bounded distributive lattices is presented as a paradigm of recognizable formal power series. Due to the idempotency properties of bounded distributive lattices, the equality of fuzzy recognizable languages is decidable, the determinization of multi-valued automata is effective, and a pumping lemma exists. Fuzzy recognizable languages over finite and infinite words are expressively equivalent to sentences of the multi-valued monadic second-order logic. Fuzzy recognizability over bounded ℓ-monoids and residuated lattices is briefly reported. The chapter concludes with two applications of fuzzy recognizable languages to real world problems in medicine.

  5. Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

    Directory of Open Access Journals (Sweden)

    Vicenc Torra

    2008-01-01

    Full Text Available WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them.

  6. Parameter identification of the glazed photovoltaic thermal system using Genetic Algorithm–Fuzzy System (GA–FS) approach and its comparative study

    International Nuclear Information System (INIS)

    Singh, Sonveer; Agrawal, Sanjay

    2015-01-01

    Highlights: • Optimization using Genetic Algorithm–Fuzzy System approach. • Overall exergy efficiency has been evaluated with different optimization tools. • Comparative analysis has been done. • GA–FS is very efficient and fast technique. • Overall exergy efficiency has been improved. - Abstract: In this paper, Genetic Algorithm–Fuzzy System (GA–FS) approach is used to identify the optimized parameters of the glazed photovoltaic thermal (PVT) system and to improve its overall exergy efficiency. The fuzzy knowledge base is used to improve the efficiency of Genetic Algorithm (GA). It is observed that three GA parameters, namely: (i) crossover probability (P cross ), (ii) mutation probability (P mut ) and (iii) population size are changing dynamically during the program, according to fuzzy knowledge base to maximize the efficiency of the GA. Here, overall exergy efficiency is considered as an objective function during the optimization process for GA–FS approach. The effort has been made to identify the different optimized parameters like; length and depth of the channel, velocity of flowing fluid, overall heat transfer coefficient from solar cell to ambient and flowing fluid and overall back loss heat transfer coefficient from flowing fluid to the ambient to maximize the overall exergy efficiency using GA–FS approach. Performance of glazed PVT using GA–FS approach has been compared with performance using GA approach and without GA. It has also been observed that the GA–FS approach is a better approach as compared to GA approach because it converges faster as compare to GA because the use of the fuzzy knowledge base with GA and take less time for identification of optimized system parameters.

  7. An improved TOPSIS with weighted hesitant vague information

    International Nuclear Information System (INIS)

    Zhou, Shenghan; Liu, Wei; Chang, Wenbing

    2016-01-01

    The selection of the best alternatives in project management has attracted increasing attention due to the uncertain environment. Vague TOPSIS is one of the powerful methods to solve this problem. In this work, firstly, a method of measuring the similarities of vague set which can take the uncertainty preference into account is raised and comparison between methods has been made to verify its effectiveness. Then, a vague set based TOPSIS in group decision is proposed to aid the decision making in project management. In this method, the weights of the experts for different criteria in the group decision are completely unknown and are calculated with the similarities of the judgments by them in the project. Finally, a computation example is shown to illustrate the method.

  8. Implementation of Steiner point of fuzzy set.

    Science.gov (United States)

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

    This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

  9. Sistem Pendukung Keputusan Pemilihan Subkontrak Menggunakan Metode Entropy dan TOPSIS

    Directory of Open Access Journals (Sweden)

    Jamila Jamila

    2011-07-01

    Full Text Available Abstract— Outsourcing is a part of production process of manufacturing industry which contribute for suitainability of a manufacture process. Choosing appropriate subcontractor which match spesification is not easy. In order to help company in determining credible subcontractors is needed a decision support system. Selection of decision support system for the production of subcontracting gloves uses Entropy and TOPSIS methods. Entropy method is used to give weight to the criteria. TOPSIS (Technique for Order Preference by Similarity to Ideal Solution method is used to select the best subcontractors, where subcontracting was elected not only has the shortest distance from the positive ideal solution but it also has the longest distance from the negative ideal solution. Designing of systems use ERD and DFD for identifying the needs of users and systems, and as for guiding the software implementation. The results of this research are the establishment of an application used to select subcontractors based on established criteria. Test results on the application can provide decision input/suggestion, although the criteria used in making decision is different. Subcontract selection decision support system can be an alternative to choose subcontractors for the production of gloves in PT. Adi Satria Abadi Yogyakarta. Keywords— DSS, Decision Support  System,  Entropy, TOPSIS, Subcontract

  10. A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications.

    Science.gov (United States)

    Costa, Daniel G; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

    2017-01-05

    The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field.

  11. MODELING OF INVESTMENT STRATEGIES IN STOCKS MARKETS: AN APPROACH FROM MULTI AGENT BASED SIMULATION AND FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    ALEJANDRO ESCOBAR

    2010-01-01

    Full Text Available This paper presents a simulation model of a complex system, in this case a financial market, using a MultiAgent Based Simulation approach. Such model takes into account microlevel aspects like the Continuous Double Auction mechanism, which is widely used within stock markets, as well as investor agents reasoning who participate looking for profits. To model such reasoning several variables were considered including general stocks information like profitability and volatility, but also some agent's aspects like their risk tendency. All these variables are incorporated throughout a fuzzy logic approach trying to represent in a faithful manner the kind of reasoning that nonexpert investors have, including a stochastic component in order to model human factors.

  12. A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2017-10-01

    Full Text Available The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of such applications, and the Dempster–Shafer evidence theory is employed to improve the system performance; whereas, it may generate a counter-intuitive result when the pieces of evidence highly conflict with each other. To handle this problem, a novel multi-sensor data fusion approach on the basis of the distance of evidence, belief entropy and fuzzy preference relation analysis is proposed. A function of evidence distance is first leveraged to measure the conflict degree among the pieces of evidence; thus, the support degree can be obtained to represent the reliability of the evidence. Next, the uncertainty of each piece of evidence is measured by means of the belief entropy. Based on the quantitative uncertainty measured above, the fuzzy preference relations are applied to represent the relative credibility preference of the evidence. Afterwards, the support degree of each piece of evidence is adjusted by taking advantage of the relative credibility preference of the evidence that can be utilized to generate an appropriate weight with respect to each piece of evidence. Finally, the modified weights of the evidence are adopted to adjust the bodies of the evidence in the advance of utilizing Dempster’s combination rule. A numerical example and a practical application in fault diagnosis are used as illustrations to demonstrate that the proposal is reasonable and efficient in the management of conflict and fault diagnosis.

  13. Constructing the Indicators of Assessing Human Vulnerability to Industrial Chemical Accidents: A Consensus-based Fuzzy Delphi and Fuzzy AHP Approach.

    Science.gov (United States)

    Fatemi, Farin; Ardalan, Ali; Aguirre, Benigno; Mansouri, Nabiollah; Mohammadfam, Iraj

    2017-04-10

    Industrial chemical accidents have been increased in developing countries. Assessing the human vulnerability in the residents of industrial areas is necessary for reducing the injuries and causalities of chemical hazards. The aim of this study was to explore the key indicators for the assessment of human vulnerability in the residents living near chemical installations. The indicators were established in the present study based on the Fuzzy Delphi method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP). The reliability of FDM and FAHP was calculated. The indicators of human vulnerability were explored in two sets of social and physical domains. Thirty-five relevant experts participated in this study during March-July 2015. According to experts, the top three indicators of human vulnerability according to the FDM and FAHP were vulnerable groups, population density, and awareness. Detailed sub-vulnerable groups and awareness were developed based on age, chronic or severe diseases, disability, first responders, and residents, respectively. Each indicator and sub-indicator was weighted and ranked and had an acceptable consistency ratio. The importance of social vulnerability indicators are about 7 times more than physical vulnerability indicators. Among the extracted indicators, vulnerable groups had the highest weight and the greatest impact on human vulnerability. however, further research is needed to investigate the applicability of established indicators and generalizability of the results to other studies. Fuzzy Delphi; Fuzzy AHP; Human vulnerability; Chemical hazards.

  14. Neuro-fuzzy system modeling based on automatic fuzzy clustering

    Institute of Scientific and Technical Information of China (English)

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

    A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

  15. Block level energy planning for domestic lighting - a multi-objective fuzzy linear programming approach

    Energy Technology Data Exchange (ETDEWEB)

    Jana, C. [Indian Inst. of Social Welfare and Business Management, Kolkata (India); Chattopadhyay, R.N. [Indian Inst. of Technology, Kharagpur (India). Rural Development Centre

    2004-09-01

    Creating provisions for domestic lighting is important for rural development. Its significance in rural economy is unquestionable since some activities, like literacy, education and manufacture of craft items and other cottage products are largely dependent on domestic lighting facilities for their progress and prosperity. Thus, in rural energy planning, domestic lighting remains a key sector for allocation of investments. For rational allocation, decision makers need alternative strategies for identifying adequate and proper investment structure corresponding to appropriate sources and precise devices. The present study aims at designing a model of energy utilisation by developing a decision support frame for an optimised solution to the problem, taking into consideration four sources and six devices suitable for the study area, namely Narayangarh Block of Midnapore District in India. Since the data available from rural and unorganised sectors are often ill-defined and subjective in nature, many coefficients are fuzzy numbers, and hence several constraints appear to be fuzzy expressions. In this study, the energy allocation model is initiated with three separate objectives for optimisation, namely minimising the total cost, minimising the use of non-local sources of energy and maximising the overall efficiency of the system. Since each of the above objective-based solutions has relevance to the needs of the society and economy, it is necessary to build a model that makes a compromise among the three individual solutions. This multi-objective fuzzy linear programming (MOFLP) model, solved in a compromising decision support frame, seems to be a more rational alternative than single objective linear programming model in rural energy planning. (author)

  16. Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network

    DEFF Research Database (Denmark)

    Govindan, Kannan; Darbari, Jyoti Dhingra; Agarwal, Vernika

    2017-01-01

    into the decision making process by selecting environmentally responsible suppliers to procure components based on sustainable criteria, choosing appropriate recovery options for end-of-use (EOU) inkjet printers, and planning an efficient transportation network design for reducing the carbon emission...... activities. A weighted fuzzy mathematical programming approach is utilised for generating a fuzzy, properly efficient solution as the desired compromised solution for the CLSC network problem configuration. The relevance of the model is justified using a real data set derived from a case study of the firm...... with higher sustainable performance and vehicles with lesser emission rate could substantially enhance firm's sustainable image and result in higher profits in the future....

  17. Fuzzy data analysis

    CERN Document Server

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  18. An efficient Neuro-Fuzzy approach to nuclear power plant transient identification

    Energy Technology Data Exchange (ETDEWEB)

    Gomes da Costa, Rafael [Instituto de Engenharia Nuclear - CNEN, Programa de Pos-Graduacao em Ciencia e Tecnologia Nucleares, Via Cinco, s/no, Cidade Universitaria, Rua Helio de Almeida, 75, Postal Box 68550, Zip Code 21941-906 Rio de Janeiro (Brazil); Abreu Mol, Antonio Carlos de, E-mail: mol@ien.gov.br [Instituto de Engenharia Nuclear - CNEN, Programa de Pos-Graduacao em Ciencia e Tecnologia Nucleares, Via Cinco, s/no, Cidade Universitaria, Rua Helio de Almeida, 75, Postal Box 68550, Zip Code 21941-906 Rio de Janeiro (Brazil); Instituto Nacional de C and T de Reatores Nucleares Inovadores (Brazil); Carvalho, Paulo Victor R. de, E-mail: paulov@ien.gov.br [Instituto de Engenharia Nuclear - CNEN, Programa de Pos-Graduacao em Ciencia e Tecnologia Nucleares, Via Cinco, s/no, Cidade Universitaria, Rua Helio de Almeida, 75, Postal Box 68550, Zip Code 21941-906 Rio de Janeiro (Brazil); Lapa, Celso Marcelo Franklin, E-mail: lapa@ien.gov.br [Instituto de Engenharia Nuclear - CNEN, Programa de Pos-Graduacao em Ciencia e Tecnologia Nucleares, Via Cinco, s/no, Cidade Universitaria, Rua Helio de Almeida, 75, Postal Box 68550, Zip Code 21941-906 Rio de Janeiro (Brazil); Instituto Nacional de C and T de Reatores Nucleares Inovadores (Brazil)

    2011-06-15

    Highlights: > We investigate a Neuro-Fuzzy modeling tool use for able transient identification. > The prelusive transient type identification is done by an artificial neural network. > After, the fuzzy-logic system analyzes the results emitting reliability degree of it. > The research support was made in a PWR simulator at the Brazilian Nuclear Engineering Institute. > The results show the potential to help operators' decisions in a nuclear power plant. - Abstract: Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the 'don't know' as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute

  19. A new approach to analyze strategy map using an integrated BSC and FUZZY DEMATEL

    Directory of Open Access Journals (Sweden)

    Seyed Abdollah Heydariyeh

    2012-01-01

    Full Text Available Today, with ever-increasing competition in global economic conditions, the necessity of effective implementation of strategy map has become an inevitable and necessary. The strategy map represents a general and structured framework for strategic objectives and plays an important role in forming competitive advantages for organizations. It is important to find important factors influencing strategy map and prioritize them based on suitable factors. In this paper, we propose an integration of BSC and Fuzzy DEMATEL technique to rank different items influencing strategy of a production plan. The proposed technique is implemented for real-world case study of glass production.

  20. Behavioural Present Value Defined as Fuzzy Number – a New Approach

    Directory of Open Access Journals (Sweden)

    Piasecki Krzysztof

    2015-12-01

    Full Text Available The behavioural present value is defined as a fuzzy number assessed under the impact of chosen behavioural factors. The first formal model turned out to be burdened with some formal defects which are finally corrected in the presented article. In this way a new modified formal model of a behavioural present value is obtained. New model of the behavioural present value is used to explain the phenomenon of market equilibrium on the efficient financial market remaining in the state of financial imbalance. These considerations are illustrated by means of extensive numerical case study.

  1. An efficient Neuro-Fuzzy approach to nuclear power plant transient identification

    International Nuclear Information System (INIS)

    Gomes da Costa, Rafael; Abreu Mol, Antonio Carlos de; Carvalho, Paulo Victor R. de; Lapa, Celso Marcelo Franklin

    2011-01-01

    Highlights: → We investigate a Neuro-Fuzzy modeling tool use for able transient identification. → The prelusive transient type identification is done by an artificial neural network. → After, the fuzzy-logic system analyzes the results emitting reliability degree of it. → The research support was made in a PWR simulator at the Brazilian Nuclear Engineering Institute. → The results show the potential to help operators' decisions in a nuclear power plant. - Abstract: Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the 'don't know' as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute (IEN

  2. A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

    Directory of Open Access Journals (Sweden)

    Błaszczuk Artur

    2017-03-01

    Full Text Available The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131-1156 K and 1.93-6.32 kg/m3, respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109-241 W/(m2K and 111-240 W/(m2K, for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.

  3. Priority Determination for Higher Education Strategic Planning Using Balanced Scorecard, FAHP and TOPSIS (Case study: XYZ University)

    Science.gov (United States)

    Yudatama, Uky; Sarno, Riyanarto

    2016-01-01

    The process of strategic planning is needed by a higher education in some cases, especially in preparing to face the challenges and competition. The results of strategic planning will help the higher education to provide a framework for achieving a competitive advantage as well as determine the direction of future policy in accordance with the desired objectives. In recent decades, the Balanced Scorecard has been applied in the field of information technology as a very popular tool and is used extensively, because it is a model that can explain between information technologies with "Business Objectives" in a comprehensive manner. This study uses 4 perspectives in the Balanced Scorecard and 7 standards in higher education quality assessment as sub-criteria. Fuzzy AHP and Fuzzy TOPSIS are used to determine the priority as making strategic policy recommendations in a higher education. The final result of this research shows the score of Customer Perspective 0.35365 is higher than other perspective, while the score in Research and Student Affairs gains significant score when compared with the others, namely 0.69753948 is also higher. This means that both of them get very serious attention as a strategic planning basis for policy making.

  4. Risk management in medical product development process using traditional FMEA and fuzzy linguistic approach: a case study

    Science.gov (United States)

    Kirkire, Milind Shrikant; Rane, Santosh B.; Jadhav, Jagdish Rajaram

    2015-12-01

    Medical product development (MPD) process is highly multidisciplinary in nature, which increases the complexity and the associated risks. Managing the risks during MPD process is very crucial. The objective of this research is to explore risks during MPD in a dental product manufacturing company and propose a model for risk mitigation during MPD process to minimize failure events. A case study approach is employed. The existing MPD process is mapped with five phases of the customized phase gate process. The activities during each phase of development and risks associated with each activity are identified and categorized based on the source of occurrence. The risks are analyzed using traditional Failure mode and effect analysis (FMEA) and fuzzy FMEA. The results of two methods when compared show that fuzzy approach avoids the duplication of RPNs and helps more to convert cognition of experts into information to get values of risk factors. The critical, moderate, low level and negligible risks are identified based on criticality; risk treatments and mitigation model are proposed. During initial phases of MPD, the risks are less severe, but as the process progresses the severity of risks goes on increasing. The MPD process should be critically designed and simulated to minimize the number of risk events and their severity. To successfully develop the products/devices within the manufacturing companies, the process risk management is very essential. A systematic approach to manage risks during MPD process will lead to the development of medical products with expected quality and reliability. This is the first research of its kind having focus on MPD process risks and its management. The methodology adopted in this paper will help the developers, managers and researchers to have a competitive edge over the other companies by managing the risks during the development process.

  5. Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

    Science.gov (United States)

    Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

    2010-10-01

    To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

  6. An ERP Selection Framework in Constructor Companies using Fuzzy AHP Approach

    Directory of Open Access Journals (Sweden)

    mohammad ali Shahhosseini

    2013-07-01

    Full Text Available The success in ERP implementation is definitely based on selecting an appropriate system which is more aligned with enterprise culture, infrastructure and requirements, and that's why ERP selection, the process and impressive criteria have been increasingly attended in recent years. The constructor companies are strongly affected by ERP systems. A successful implementation will improve their productivity and promote their performance considerably. However, it is a challenge for decision-makers to identify the real needs, define the criteria, select the acceptable vendor and purchase the most appropriate system. This study is developed to present a Fuzzy AHP-based framework for selecting ERP systems in constructor companies. In this study, the impressive criteria have been collected by reviewing previous studies and researches, a questionnaire was used to assess and define the criteria and sub-criteria’s priority. Afterward, another questionnaire was used to compare the alternatives regarding to each criteria. Eventually, the Fuzzy Analytic Hierarchical Process was used to select a system which is more aligned with the organization’s requirements and strategies

  7. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    International Nuclear Information System (INIS)

    Kucukali, Serhat; Baris, Kemal

    2010-01-01

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

  8. Multi-attribute Reverse Auction Design Based on Fuzzy Data Envelopment Analysis Approach

    Directory of Open Access Journals (Sweden)

    Deyan Chen

    2017-08-01

    Full Text Available Multi-attribute reverse auction is widely used for the procurements of enterprises or governments. To overcome the difficulty of identifying bidding attribute weight and score function of the buyer, the multi-round auction and bidding models with multiple winners are established based on fuzzy data envelopment analysis. The winner determination model of the buyer considers the integrated input-output efficiency of k winners. The bidding strategy of seller is divided into two parts: the first one estimates the weight of the ideal supplier that is thought to be the buyer’s preference; the second one is to calculate the weight of the test supplier which reflects the change trend of current weights and the seller’s weakness. The final predicted weight is the weighted sum of both. On the basis of known weight, the test supplier can improve his efficiency to increase the winning chance in the next round auction. Our models comprise crisp numbers and fuzzy numbers. Finally, a numerical example verifies the validity of the proposed models.

  9. RFM-based eco-efficiency analysis using Takagi-Sugeno fuzzy and AHP approach

    International Nuclear Information System (INIS)

    Chen Ruiyang

    2009-01-01

    Eco-design is crucial to take environmental aspects into account in the phases of design. Few literature review that green product must meet market value. The development of models to predict market value is thus very useful because it can provide early eco-efficiency to the eco-design. For the eco-design engineer, when he tries to solve a customer feedback problem, he usually faces the eco-efficiency. There are, however, often other types of fuzziness uncertainty present, which are related to the quantity of eco-design conditions. In this paper, it is derived that analysis of eco-efficiency can be identified by using the RFM value for quantifying eco-design with Takagi-Sugeno fuzzy system on customer feedback problem. It clusters eco-efficiency into segments according to green product usages value expressed in terms of weighted RFM. This experiment examined the weighted RFM effect of overall average normalized, AHP and non-weighted for F1 metric. The experimental results show that the proposed methodology indeed can yield identification of higher quality

  10. Fuzzy VIKOR approach for selection of big data analyst in procurement management

    Directory of Open Access Journals (Sweden)

    Surajit Bag

    2016-07-01

    Full Text Available Background: Big data and predictive analysis have been hailed as the fourth paradigm of science. Big data and analytics are critical to the future of business sustainability. The demand for data scientists is increasing with the dynamic nature of businesses, thus making it indispensable to manage big data, derive meaningful results and interpret management decisions. Objectives: The purpose of this study was to provide a brief conceptual review of big data and analytics and further illustrate the use of a multicriteria decision-making technique in selecting the right skilled candidate for big data and analytics in procurement management. Method: It is important for firms to select and recruit the right data analyst, both in terms of skills sets and scope of analysis. The nature of such a problem is complex and multicriteria decision-making, which deals with both qualitative and quantitative factors. In the current study, an application of the Fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR method was used to solve the big data analyst selection problem. Results: From this study, it was identified that Technical knowledge (C1, Intellectual curiosity (C4 and Business acumen (C5 are the strongest influential criteria and must be present in the candidate for the big data and analytics job. Conclusion: Fuzzy VIKOR is the perfect technique in this kind of multiple criteria decisionmaking problematic scenario. This study will assist human resource managers and procurement managers in selecting the right workforce for big data analytics.

  11. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Kucukali, Serhat [Civil Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey); Baris, Kemal [Mining Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey)

    2010-05-15

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning. (author)

  12. Possible use of fuzzy logic in database

    Directory of Open Access Journals (Sweden)

    Vaclav Bezdek

    2011-04-01

    Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.

  13. The majority rule in a fuzzy environment.

    OpenAIRE

    Montero, Javier

    1986-01-01

    In this paper, an axiomatic approach to rational decision making in a fuzzy environment is studied. In particular, the majority rule is proposed as a rational way for aggregating fuzzy opinions in a group, when such agroup is defined as a fuzzy set.

  14. Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

    Directory of Open Access Journals (Sweden)

    Saeed Khalili

    2014-08-01

    Full Text Available In the past, different methods for asset depreciation have been defined but most of these procedures deal with certain parameters and inputs. The availability of certain parameters in many real world situations is difficult and sometimes impossible. The primary objective of this paper is to obtain methods for calculating depreciation where some of the defined parameters are under uncertainty. Hence, by using the fuzzy science basics, extension principle and α-cut technique, we rewrite some classic methods for calculating depreciation in fuzzy form. Then, for comparing the methods of fuzzy depreciation under uncertain conditions by using the formula of calculating the Fuzzy Present worth (FPW, the Present worth of Tax saving (PWTS of any aforementioned methods has been obtained. Finally, since the amount of tax savings achieved for each of the methods is a fuzzy number, one of the fuzzy prioritization methods is used in order to select the best depreciation technique.

  15. Fuzzy upper bounds and their applications

    Energy Technology Data Exchange (ETDEWEB)

    Soleimani-damaneh, M. [Department of Mathematics, Faculty of Mathematical Science and Computer Engineering, Teacher Training University, 599 Taleghani Avenue, Tehran 15618 (Iran, Islamic Republic of)], E-mail: soleimani_d@yahoo.com

    2008-04-15

    This paper considers the concept of fuzzy upper bounds and provides some relevant applications. Considering a fuzzy DEA model, the existence of a fuzzy upper bound for the objective function of the model is shown and an effective approach to solve that model is introduced. Some dual interpretations are provided, which are useful for practical purposes. Applications of the concept of fuzzy upper bounds in two physical problems are pointed out.

  16. Neuro-fuzzy Control of Integrating Processes

    Directory of Open Access Journals (Sweden)

    Anna Vasičkaninová

    2011-11-01

    Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.

  17. Comparison of Multi-Criteria Decision Support Methods (AHP, TOPSIS, SAW & PROMENTHEE) for Employee Placement

    Science.gov (United States)

    Widianta, M. M. D.; Rizaldi, T.; Setyohadi, D. P. S.; Riskiawan, H. Y.

    2018-01-01

    The right decision in placing employees in an appropriate position in a company will support the quality of management and will have an impact on improving the quality of human resources of the company. Such decision-making can be assisted by an approach through the Decision Support System (DSS) to improve accuracy in the employee placement process. The purpose of this paper is to compare the four methods of Multi Criteria Decision Making (MCDM), ie Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Of Evaluations (PROMETHEE) for the application of employee placement in accordance with predetermined criteria. The ranking results and the accuracy level obtained from each method are different depending on the different scaling and weighting processes in each method.

  18. Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

    Science.gov (United States)

    Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh

    2017-07-01

    In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

  19. Fuzzy linguistic model for interpolation

    International Nuclear Information System (INIS)

    Abbasbandy, S.; Adabitabar Firozja, M.

    2007-01-01

    In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method

  20. Fuzzy Control Teaching Models

    Directory of Open Access Journals (Sweden)

    Klaus-Dietrich Kramer

    2016-05-01

    Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

  1. Relational Demonic Fuzzy Refinement

    Directory of Open Access Journals (Sweden)

    Fairouz Tchier

    2014-01-01

    Full Text Available We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join (⊔fuz, fuzzy demonic meet (⊓fuz, and fuzzy demonic composition (□fuz. Our definitions and properties are illustrated by some examples using mathematica software (fuzzy logic.

  2. Fuzzy-neural approaches to the prediction of disruptions in ASDEX Upgrade

    International Nuclear Information System (INIS)

    Morabito, F.C.; Versaci, M.; Pautasso, G.; Tichmann, C.

    2001-01-01

    Disruption is a sudden loss of magnetic confinement that can cause damage to the machine walls and support structures. For this reason, it is of practical interest to be able to detect the onset of such an event early. A novel technique is presented of early prediction of plasma disruption in tokamak reactors which uses neural networks and 'fuzzy' inference. The studies carried out in the work make use of an experimental database of disruptive shots made available by the ASDEX Upgrade Team. The main result of the work is that, in the limit of the available database, it is possible to predict the onset of the disruptive event sufficiently in advance in order to put the control system into action. The proposed system is a modular scheme that exploits a decomposition of the original database carried out in a proper way. (author)

  3. FUZZY THERMOECONOMIC APPROACH TO NANOFLUID SELECTION IN VAPOR COMPRESSION REFRIGERATION CYCLE

    Directory of Open Access Journals (Sweden)

    D. Kuleshov

    2014-06-01

    Full Text Available The working fluid selection in the vapour compression refrigeration cycles has been studied as a fuzzy thermoeconomic optimization problem. Three criteria: thermodynamic (COP Coefficient Of Performance, economic (LCC Life Cycle Cost, and ecologic (GWP – Global Warming Potential are chosen as target functions. The decision variables X as an information characteristics of desired refrigerant are presented by its critical parameters and normal boiling temperature. Local criteria are expressed via thermodynamic properties restored from information characteristics of refrigerant X, as well as life cycle costs are calculated by the standard economic relationships. GWP values are taken from the refrigerant database. Class of substances under consideration is presented by the natural refrigerant R600a embedded with nanostructured materials.

  4. Fuzzy Similarity Measures Approach in Benchmarking Taxonomies of Threats against SMEs in Developing Economies

    DEFF Research Database (Denmark)

    Yeboah-Boateng, Ezer Osei

    2013-01-01

    There are various threats that militate against SMEs in developing economies. However, most SMEs fall on the conservative “TV News Effect” of most-publicized cyber-threats or incidences, with disproportionate mitigation measures. This paper endeavors to establish a taxonomy of threat agents to fill...... in the void. Various fuzzy similarity measures based on multi-attribute decision-making techniques have been employed in the evaluation. The taxonomy offers a panoramic view of cyber-threats in assessing mission-critical assets, and serves as a benchmark for initiating appropriate mitigation strategies. SMEs...... in developing economies were strategically interviewed for their expert opinions on various business and security metrics. The study established that natural disasters, which are perennial in most developing economies, are the most critical cyber-threat agent, whilst social engineering is the least critical...

  5. Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps

    Directory of Open Access Journals (Sweden)

    Farinaz Behrooz

    2018-02-01

    Full Text Available Heating, Ventilating, and Air Conditioning (HVAC systems are the major energy-consuming devices in buildings. Nowadays, due to the high demand for HVAC system installation in buildings, designing an effective controller in order to decrease the energy consumption of the devices while meeting the thermal comfort demands in buildings are the most important goals of control designers. The purpose of this article is to investigate the different control methods for Heating, Ventilating, and Air Conditioning and Refrigeration (HVAC & R systems. The advantages and disadvantages of each control method are discussed and finally the Fuzzy Cognitive Map (FCM method is introduced as a new strategy for HVAC systems. The FCM method is an intelligent and advanced control technique to address the nonlinearity, Multiple-Input and Multiple-Output (MIMO, complexity and coupling effect features of the systems. The significance of this method and improvements by this method are compared with other methods.

  6. A new web-based framework development for fuzzy multi-criteria group decision-making.

    Science.gov (United States)

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

  7. Digital modelling of landscape and soil in a mountainous region: A neuro-fuzzy approach

    Science.gov (United States)

    Viloria, Jesús A.; Viloria-Botello, Alvaro; Pineda, María Corina; Valera, Angel

    2016-01-01

    Research on genetic relationships between soil and landforms has largely improved soil mapping. Recent technological advances have created innovative methods for modelling the spatial soil variation from digital elevation models (DEMs) and remote sensors. This generates new opportunities for the application of geomorphology to soil mapping. This study applied a method based on artificial neural networks and fuzzy clustering to recognize digital classes of land surfaces in a mountainous area in north-central Venezuela. The spatial variation of the fuzzy memberships exposed the areas where each class predominates, while the class centres helped to recognize the topographic attributes and vegetation cover of each class. The obtained classes of terrain revealed the structure of the land surface, which showed regional differences in climate, vegetation, and topography and landscape stability. The land-surface classes were subdivided on the basis of the geological substratum to produce landscape classes that additionally considered the influence of soil parent material. These classes were used as a framework for soil sampling. A redundancy analysis confirmed that changes of landscape classes explained the variation in soil properties (p = 0.01), and a Kruskal-Wallis test showed significant differences (p = 0.01) in clay, hydraulic conductivity, soil organic carbon, base saturation, and exchangeable Ca and Mg between classes. Thus, the produced landscape classes correspond to three-dimensional bodies that differ in soil conditions. Some changes of land-surface classes coincide with abrupt boundaries in the landscape, such as ridges and thalwegs. However, as the model is continuous, it disclosed the remaining variation between those boundaries.

  8. A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

    2017-07-01

    For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other

  9. 视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach

    Institute of Scientific and Technical Information of China (English)

    张一巍; 黄源清

    2002-01-01

    The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.

  10. Mapping Diversity of Publication Patterns in the Social Sciences and Humanities: An Approach Making Use of Fuzzy Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Frederik T. Verleysen

    2016-11-01

    Full Text Available Purpose: To present a method for systematically mapping diversity of publication patterns at the author level in the social sciences and humanities in terms of publication type, publication language and co-authorship. Design/methodology/approach: In a follow-up to the hard partitioning clustering by Verleysen and Weeren in 2016, we now propose the complementary use of fuzzy cluster analysis, making use of a membership coefficient to study gradual differences between publication styles among authors within a scholarly discipline. The analysis of the probability density function of the membership coefficient allows to assess the distribution of publication styles within and between disciplines. Findings: As an illustration we analyze 1,828 productive authors affiliated in Flanders, Belgium. Whereas a hard partitioning previously identified two broad publication styles, an international one vs. a domestic one, fuzzy analysis now shows gradual differences among authors. Internal diversity also varies across disciplines and can be explained by researchers' specialization and dissemination strategies. Research limitations: The dataset used is limited to one country for the years 2000-2011; a cognitive classification of authors may yield a different result from the affiliation-based classification used here. Practical implications: Our method is applicable to other bibliometric and research evaluation contexts, especially for the social sciences and humanities in non-Anglophone countries. Originality/value: The method proposed is a novel application of cluster analysis to the field of bibliometrics. Applied to publication patterns at the author level in the social sciences and humanities, for the first time it systematically documents intra-disciplinary diversity.

  11. Captive power plant selection for pakistan cement industry in perspective of current energy crises: a fuzzy-ahp approach

    International Nuclear Information System (INIS)

    Ali, H.M.; Sultan, A.; Rana, B.B.

    2017-01-01

    Based on the prevailing energy crisis, it is reasonable for the Cement industry of Pakistan to look for alternate sources of electricity generation. The decision of selecting a CPP (Captive Power Plant) depends on a broad variety of parameters which may be conflicting to each other. A comparative evaluation of these CPP's should be helpful for industry, particularly if the applied methodology can handle with the real world ambiguities and imprecisions associated with the data pools and expert opinions. This paper utilizes an F-AHP (Fuzzy Analytical Hierarchy Process) based multi-attribute framework to prioritize the affecting parameters and assign rankings to the CPP alternatives. The CPP's recommended by experts for this study are RDF-CPP (Refused Derived Fuel CPP), CF-CPP (Coal Fired CPP) and WHR-CPP (Waste Heat Recovery CPP). The factors affecting the decision of selecting the optimum CPP are prioritized by the experts using our F-AHP approach. Real world quantitative data is extracted from different online resources and financial reports of cement companies in Pakistan. The F-AHP model is flexible enough to deal with a variety of inputs including qualitative scales, crisp values and standard fuzzy numbers. The model is solved and a sensitivity analysis is performed in respective software. This study shows that non-conventional CPPs are highly demanded for cement industry in Pakistan and while selecting these CPPs, management gives high priority to factors like 'automation' and 'environment' whereas associated "initial cost"is not given much weight in decision making. In concluding ranking list, WHR-CPP is at the top and CF-CPP is at the bottom. This study may facilitate decision makers of cement industry in Pakistan and international CPP manufacturers alike in their forthcoming strategic decisions. (author)

  12. On the Fuzzy Convergence

    Directory of Open Access Journals (Sweden)

    Abdul Hameed Q. A. Al-Tai

    2011-01-01

    Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.

  13. Fuzzy Commitment

    Science.gov (United States)

    Juels, Ari

    The purpose of this chapter is to introduce fuzzy commitment, one of the earliest and simplest constructions geared toward cryptography over noisy data. The chapter also explores applications of fuzzy commitment to two problems in data security: (1) secure management of biometrics, with a focus on iriscodes, and (2) use of knowledge-based authentication (i.e., personal questions) for password recovery.

  14. Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory

    NARCIS (Netherlands)

    Cornelissen, A.M.G.; Berg, van den J.; Koops, W.J.; Grossman, M.; Udo, H.M.J.

    2001-01-01

    As a consequence of the impact of sustainability on agricultural production systems, a standardized framework to monitor sustainable development would have great practical utility. The objective of this paper is to introduce fuzzy set theory and develop fuzzy mathematical models to assess

  15. A Maximin Approach for the Bi-criteria 0-1 Random Fuzzy Programming Problem Based on the Necessity Measure

    International Nuclear Information System (INIS)

    Hasuike, Takashi; Ishii, Hiroaki; Katagiri, Hideki

    2009-01-01

    This paper considers a bi-criteria general 0-1 random fuzzy programming problem based on the degree of necessity which include some previous 0-1 stochastic and fuzzy programming problems. The proposal problem is not well-defined due to including randomness and fuzziness. Therefore, by introducing chance constraint and fuzzy goals for objectives, and considering the maximization of the aspiration level for total profit and the degree of necessity that the objective function's value satisfies the fuzzy goal, the main problem is transformed into a deterministic equivalent problem. Furthermore, by using the assumption that each random variable is distributed according to a normal distribution, the problem is equivalently transformed into a basic 0-1 programming problem, and the efficient strict solution method to find an optimal solution is constructed.

  16. A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Dipak Kumar Jana

    2013-01-01

    Full Text Available An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA and fuzzy simulation-based genetic algorithm (FSGA are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and high-tech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon.

  17. Analyzing the impact of social factors on homelessness: a fuzzy cognitive map approach.

    Science.gov (United States)

    Mago, Vijay K; Morden, Hilary K; Fritz, Charles; Wu, Tiankuang; Namazi, Sara; Geranmayeh, Parastoo; Chattopadhyay, Rakhi; Dabbaghian, Vahid

    2013-08-23

    The forces which affect homelessness are complex and often interactive in nature. Social forces such as addictions, family breakdown, and mental illness are compounded by structural forces such as lack of available low-cost housing, poor economic conditions, and insufficient mental health services. Together these factors impact levels of homelessness through their dynamic relations. Historic models, which are static in nature, have only been marginally successful in capturing these relationships. Fuzzy Logic (FL) and fuzzy cognitive maps (FCMs) are particularly suited to the modeling of complex social problems, such as homelessness, due to their inherent ability to model intricate, interactive systems often described in vague conceptual terms and then organize them into a specific, concrete form (i.e., the FCM) which can be readily understood by social scientists and others. Using FL we converted information, taken from recently published, peer reviewed articles, for a select group of factors related to homelessness and then calculated the strength of influence (weights) for pairs of factors. We then used these weighted relationships in a FCM to test the effects of increasing or decreasing individual or groups of factors. Results of these trials were explainable according to current empirical knowledge related to homelessness. Prior graphic maps of homelessness have been of limited use due to the dynamic nature of the concepts related to homelessness. The FCM technique captures greater degrees of dynamism and complexity than static models, allowing relevant concepts to be manipulated and interacted. This, in turn, allows for a much more realistic picture of homelessness. Through network analysis of the FCM we determined that Education exerts the greatest force in the model and hence impacts the dynamism and complexity of a social problem such as homelessness. The FCM built to model the complex social system of homelessness reasonably represented reality for the

  18. A HEURISTIC CASCADING FUZZY LOGIC APPROACH TO REACTIVE NAVIGATION FOR UAV

    Directory of Open Access Journals (Sweden)

    Yew-Chung Chak

    2014-12-01

    Full Text Available ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines and moving obstacles (e.g., aircraft, balloons. In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R problem, in which the control strategy is comprised of two cascading modules. The first one is Obstacle Avoidance control and the latter is Path Tracking control. Simulation results show that the proposed architecture effectively resolves the conflicts and achieve rapid movement towards the target waypoint.ABSTRAK: Keupayaan mengemudi Kenderaan Udara Tanpa Pemandu (UAV dengan selamat di kawasan yang tidak diketahui menawarkan potensi yang besar untuk aplikasi yang lebih luas dalam ruang udara yang tidak terasing. Terbang di ruang udara yang tidak terasing menimbulkan risiko perlanggaran dengan halangan statik (contohnya, menara, talian kuasa dan halangan bergerak (contohnya, pesawat udara, belon. Dalam kajian ini, kami mencadangkan satu strategi heuristik kawalan logik kabur yang melata untuk menyelesaikan masalah Pengesanan Konflik dan Penyelesaian (CD&R, di mana strategi kawalan yang terdiri daripada dua modul melata. Hasil simulasi menunjukkan bahawa seni bina yang dicadangkan berjaya menyelesaikan konflik dan mencapai penerbangan pesat ke arah titik laluan sasaran.KEYWORDS: fuzzy logic; motion planning; obstacle avoidance; path tracking; reactive navigation; UAV Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso

  19. Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

    Science.gov (United States)

    Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

    2006-01-01

    Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

  20. WHY FUZZY QUALITY?

    Directory of Open Access Journals (Sweden)

    Abbas Parchami

    2016-09-01

    Full Text Available Such as other statistical problems, we may confront with uncertain and fuzzy concepts in quality control. One particular case in process capability analysis is a situation in which specification limits are two fuzzy sets. In such a uncertain and vague environment, the produced product is not qualified with a two-valued Boolean view, but to some degree depending on the decision-maker strictness and the quality level of the produced product. This matter can be cause to a rational decision-making on the quality of the production line. First, a comprehensive approach is presented in this paper for modeling the fuzzy quality concept. Then, motivations and advantages of applying this flexible approach instead of using classical quality are mentioned.