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Sample records for fuzzy topsis approach

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

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    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. New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance

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    Mikael Collan

    2015-01-01

    Full Text Available This paper introduces new closeness coefficients for fuzzy similarity based TOPSIS. The new closeness coefficients are based on multidistance or fuzzy entropy, are able to take into consideration the level of similarity between analysed criteria, and can be used to account for the consistency or homogeneity of, for example, performance measuring criteria. The commonly known OWA operator is used in the aggregation process over the fuzzy similarity values. A range of orness values is considered in creating a fuzzy overall ranking for each object, after which the fuzzy rankings are ordered to find a final linear ranking. The presented method is numerically applied to a research and development project selection problem and the effect of using two new closeness coefficients based on multidistance and fuzzy entropy is numerically illustrated.

  3. Equipment Selection by using Fuzzy TOPSIS Method

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    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.

  4. Rank University Websites Using Fuzzy AHP and Fuzzy TOPSIS Approach on Usability

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    Renuka Nagpal

    2015-01-01

    Full Text Available With the advent of dynamic website usually all business processes of a business organization are linked with the website of the organization. This is resulted in designing of a complex and gigantic website which may result in slow download and unfriendly navigation. Satisfying the end user need is one of the key principles of designing an effective website. As there are different users for given website, hence there are different criteria on which user wants to get satisfied, hence evaluating a website is a multi-criteria decision making problem. In order to incorporate uncertainties and vagueness in decision making Fuzzy Analytic Hierarchy (FAHP approach is extended with Fuzzy TOPSIS approach, where different decision makers (DM's opinion was considered for ranking the website.

  5. A comparative analysis between fuzzy topsis and simplified fuzzy topsis

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    Ahmad, Sharifah Aniza Sayed; Mohamad, Daud

    2017-08-01

    Fuzzy Multiple Criteria Decision Making plays an important role in solving problems in decision making under fuzzy environment. Among the popular methods used is the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) where the solution is based on the shortest distance from its positive ideal solution and the farthest distance from its negative ideal solution. The fuzzy TOPSIS method was first introduced by Chen (2000). At present, there are several variants of fuzzy TOPSIS methods and each of them claimed to have its own advantages. In this paper, a comparative analysis is made between the classical fuzzy TOPSIS method proposed by Chen in 2000 and the simplified fuzzy TOPSIS proposed by Sodhi in 2012. The purpose of this study is to show the similarities and the differences between these two methods and also elaborate on their strengths and limitations as well. A comparison is also made by providing numerical examples of both methods.

  6. A multi-criteria decision-making approach that combines fuzzy TOPSIS and DEA methodologies

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    Taylan, Osman

    2014-11-01

    Full Text Available Employee selection is a multi-criteria decision-making (MCDM problem for selecting suitable applicants from a ready pool. The selection aims to make use of their knowledge, relevant skills, and other characteristics to perform a specific job. The aim of this study is to develop a systematic approach for selecting the best candidates among the air traffic controllers (ATCs for aviation in Saudi Arabia. Three integrated methods were employed for decision-making in this study. First, a fuzzy decision tree was applied to determine the criteria weights, then the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS was employed to rank the attributes. In the last step, the Data Envelopment Analysis (DEA was used to transform the qualitative variables into quantitative equivalences. A survey was conducted by national and international decision- makers to elicit the necessary information on the criteria and sub-criteria of the air traffic control system. The decision problem was formulated by employing five criteria and ten applicants. The relationship between the fuzzy TOPSIS and fuzzy-weighted average was very positive for decision-making. The outcomes of the fuzzy TOPSIS and DEA encouraged the development of a decision support system for the selection of ATCs.

  7. A Simplified Description of Fuzzy TOPSIS

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    Sodhi, Balwinder

    2012-01-01

    A simplified description of Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) is presented. We have adapted the TOPSIS description from existing Fuzzy theory literature and distilled the bare minimum concepts required for understanding and applying TOPSIS. An example has been worked out to illustrate the application of TOPSIS for a multi-criteria group decision making scenario.

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

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    Onüt, 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.

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

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    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.

  10. Fuzzy-TOPSIS Method with Multi-goal

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    PANG Jin-hui; ZHANG Qiang

    2009-01-01

    To develop the technique for order preference by similarity to an ideal solution,namely,TOPSIS method with multi-goal in fuzzy decision environment.Firstly,a new approach to constructing fuzzy decision matrix by Choquet integral was proposed in muhi-goal decision system.Secondly,the concepts of fuzzy positive-ideal solution and fuzzy negative-ideal solution related to the fuzzy decision matrix were given.Finally,the credibility measure was adopted to calculate the distances to fuzzy positive-ideal solution and fuzzy negative-ideal solution.The presented fuzzy-TOPSIS method embodies well both the predetermined preferences and the weights of goals.

  11. The DEA and Intuitionistic Fuzzy TOPSIS Approach to Departments' Performances: A Pilot Study

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    Babak Daneshvar Rouyendegh

    2011-01-01

    Full Text Available This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis (DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated by Data Envelopment Analysis (DEA and separately formulates each pair of units. In the second stage, we use the opinion of experts to be applied into a model of group Decision-Making (DM called the Intuitionistic Fuzzy TOPSIS (IFT method. The results of both methods are then multiplied to obtain the results. DEA and Intuitionistic Fuzzy TOPSIS ranking do not replace the DEA classification model; rather, it furthers the analysis by providing full ranking in the DEA context for all units by aggregate individual opinions of decision makers for rating the importance of criteria and alternatives.

  12. Fuzzy TOPSIS for Multiresponse Quality Problems in Wafer Fabrication Processes

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    Chiun-Ming Liu

    2013-01-01

    Full Text Available The quality characteristics in the wafer fabrication process are diverse, variable, and fuzzy in nature. How to effectively deal with multiresponse quality problems in the wafer fabrication process is a challenging task. In this study, the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS, one of the fuzzy multiattribute decision-analysis (MADA methods, is proposed to investigate the fuzzy multiresponse quality problem in integrated-circuit (IC wafer fabrication process. The fuzzy TOPSIS is one of the effective fuzzy MADA methods for dealing with decision-making problems under uncertain environments. First, a fuzzy TOPSIS methodology is developed by considering the ambiguity between quality characteristics. Then, a detailed procedure for the developed fuzzy TOPSIS approach is presented to show how the fuzzy wafer fabrication quality problems can be solved. Real-world data is collected from an IC semiconductor company and the developed fuzzy TOPSIS approach is applied to find an optimal combination of parameters. Results of this study show that the developed approach provides a satisfactory solution to the wafer fabrication multiresponse problem. This developed approach can be also applied to other industries for investigating multiple quality characteristics problems.

  13. Designing of fuzzy expert heuristic models with cost management toward coordinating AHP, fuzzy TOPSIS and FIS approaches

    Indian Academy of Sciences (India)

    ANUP KUMAR RAJAK; MALAY NIRAJ; SHALENDRA KUMAR

    2016-10-01

    In genuine industrial case, problems are inescapable and pose enormous challenges to incorporate accurate sustainability factors into supplier selection. In this present study, three different primarily based multicriteria decision making fuzzy models have been compared with their deterministic version so as to resolve fuzzy prioritization problems. The developed model applies AHP, TOPSIS and fuzzy inference system (FIS)using a MATLAB toolbox to effectively analyze the interdependencies between sustainability criteria and select the best sustainable supplier in the fuzzy environment, while capturing all objective criteria. A typical supplier A4 has been awarded the most suitable supplier with 0.386 composite relative weights of AHP, relative closeness to ideal solution 0.7154 and normalized score index 0.219 FIS model using MATLAB toolbox.

  14. 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.

  15. 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

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    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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

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

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    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. AN INTEGRATED FUZZY AHP AND TOPSIS MODEL FOR SUPPLIER EVALUATION

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    Željko Stević

    2016-05-01

    Full Text Available In today’s modern supply chains, the adequate suppliers’ choice has strategic meaning for entire companies’ business. The aim of this paper is to evaluate different suppliers using the integrated model that recognizes a combination of fuzzy AHP (Analytical Hierarchy Process and the TOPSIS method. Based on six criteria, the expert team was formed to compare them, so determination of their significance is being done with fuzzy AHP method. Expert team also compares suppliers according to each criteria and on the base of triangular fuzzy numbers. Based on their inputs, TOPSIS method is used to estimate potential solutions. Suggested model accomplishes certain advantages in comparison with previously used traditional models which were used to make decisions about evaluation and choice of supplier.

  3. A Fuzzy TOPSIS based Approach for Distributor Selection in Supply Chain Management: An Empirical Study of an Agricultural Enterprise in China

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    Shi Haoran

    2014-01-01

    Full Text Available Distributor selection plays an important role in the supply chain management, particularly in the current competitive environment. The recent researches are mainly focused on the conceptual, descriptive and simulation. However, analyzing qualitative information is difficult by standard statistical analysis, which means that a proper quantitative method is desired for distributor selection in fuzzy environment. This study is an attempt to identify the factors which have impact on the distribution cost and the selection for better distributors in an agricultural enterprise in China based on fuzzy TOPSIS.

  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. 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.

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

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

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    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

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

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    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.

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

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

    2016-11-01

    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.

  11. COMPARISON OF FUZZY TOPSIS METHODS USED GROUP DECISION MAKING AND AN APPLICATION

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    FATİH ECER

    2013-06-01

    Full Text Available Fuzzy TOPSIS method used group decision making in fuzzy environment is one of the Multiple Criteria Decision Making (MCDM methods.  It is needed to decision makers (DM, alternatives and decision criteria in order to apply this method. Foundation of the method is the ideal solution is the shortest distance from Fuzzy Positive Ideal Solution (FPIS and the farthest distance from Fuzzy Negative Ideal Solution (FNIS. Using FPIS and FNIS, closeness coefficients of alternatives are evaluated. Closeness coefficients express scores of the alternatives. According to closeness coefficients, alternatives are ranked from the best to the worst. In this study, two fuzzy TOPSIS methods having different algorithms are compared. To this purpose, firstly assessments of decision makers are converted to triangular fuzzy numbers. It is seen at the end of the study that ranking orders of alternatives don’t change.

  12. Metode Quality Function Deployment Dan Fuzzy Topsis Untuk Sistem Pendukung Keputusan Pemilihan Perusahaan Penyedia Jasa Internet

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    Novianto Dwi Prasongko

    2016-01-01

    Full Text Available Internet Service Provider (ISP is a company or business organization that provides access to intenet and services related for individual consumer or companies. There are many ISP in Indonesia recently, and they have almost the same product to offered. This problem makes internet service provider selection become a major issue. Decision support system can be used to recommend the best ISP company based on need. The aim of this research is to used Quality Function Deployment with Fuzzy TOPSIS sequentially to select the best ISP company as needed, and implemented in decision support system for internet service provider selection. Quality Function Deployment and Fuzzy TOPSIS methods used to evaluate, and then recommend the ISP company by ranked. Quality Function Deployment method used to find out customers requirements about internet network, the weighting of the criteria and the assessment of each ISP company. Fuzzy TOPSIS used to rank ISP company. These two methods produce consistent ratings when sensitivity analysis is performed for fuzzy and crisp value. These two methods make decision support system result can be trusted. Keywords : Quality Function Deployment; Fuzzy TOPSIS; Sensitivity Analysis

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

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    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.

  14. Categorizing the Driving Affecting Factors on Iran’s Carpet Industry competitiveness by Fuzzy Topsis Technique

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    F. Haghshenas Kashani

    2011-01-01

    Full Text Available One of the most prominent and important problems of Iran industries is the lack of competitiveness and the major reason among several various reasons is due to the absence of a defined approach for competitiveness. During this study, by testing an integrated model and presenting it as the research final model, we are trying to categorize the driving affecting factors on Iran’s carpet industry competitiveness. Thus, one of the new Multi Criteria Decision Making (MCDM techniques – Fuzzy Topsis- was applied. The components of research conceptual model which has 3 main criteria (internal resources, market situation, and innovation strength and 44 sub criteria was categorized by Fuzzy Topsis technique. Accordingly, “market share”, “e-commerce”, “knowledge creation’, “industry reliability”, and “exporters expertise and skills” were recognized as the most important sub criteria and simultaneously “customers satisfaction”, “employees’ education”, “international certifications”, and “fundamental researches” were recognized as the least momentous and effective sub criteria. These results represent that Iran’s hand-made carpet industry has still some difficulties in applying marketing knowledge such as: on line marketing, e-commerce, and making merchants familiar to these techniques. In addition, paying excessive attention to the quality, durability, and appearance of the Iranian carpets make managers to ignore some other factors such as customer satisfaction. Among the main criteria, market-based perspective was chosen as the most leading and significant criterion. In other words, the approach of position improvement in the international markets is recommended for this industry.

  15. Categorizing the Driving Affecting Factors on Iran’s Carpet Industry competitiveness by Fuzzy Topsis Technique

    Directory of Open Access Journals (Sweden)

    Farideh Haghshenas

    2011-07-01

    One of the most prominent and important problems of Iran industries is the lack of competitiveness and the major reason among several various reasons is due to the absence of a defined approach for competitiveness. During this study, by testing an integrated model and presenting it as the research final model, we are trying to categorize the driving affecting factors on Iran’s carpet industry competitiveness. Thus, one of the new Multi Criteria Decision Making (MCDM techniques – Fuzzy Topsis- was applied. The components of research conceptual model which has 3 main criteria (internal resources, market situation, and innovation strength and 44 sub criteria was categorized by Fuzzy Topsis technique. Accordingly, “market share”, “e-commerce”, “knowledge creation’, “industry reliability”, and “exporters expertise and skills” were recognized as the most important sub criteria and simultaneously “customers satisfaction”, “employees’ education”, “international certifications”, and “fundamental researches” were recognized as the least momentous and effective sub criteria. These results represent that Iran’s hand-made carpet industry has still some difficulties in applying marketing knowledge such as: on line marketing, e-commerce, and making merchants familiar to these techniques. In addition, paying excessive attention to the quality, durability, and appearance of the Iranian carpets make managers to ignore some other factors such as customer satisfaction. Among the main criteria, market-based perspective was chosen as the most leading and significant criterion. In other words, the approach of position improvement in the international markets is recommended for this industry.

  16. The mean error estimation of TOPSIS method using a fuzzy reference models

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    Wojciech Sałabun

    2013-04-01

    Full Text Available The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS is a commonly used multi-criteria decision-making method. A number of authors have proposed improvements, known as extensions, of the TOPSIS method, but these extensions have not been examined with respect to accuracy. Accuracy estimation is very difficult because reference values for the obtained results are not known, therefore, the results of each extension are compared to one another. In this paper, the author propose a new method to estimate the mean error of TOPSIS with the use of a fuzzy reference model (FRM. This method provides reference values. In experiments involving 1,000 models, 28 million cases are simulated to estimate the mean error. Results of four commonly used normalization procedures were compared. Additionally, the author demonstrated the relationship between the value of the mean error and the nonlinearity of models and a number of alternatives.

  17. Financial Performance Evaluation of Turkish Energy Companies with Fuzzy AHP and Fuzzy TOPSIS Methods

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    Kemal Eyuboglu

    2016-07-01

    Full Text Available Turkey’s economy has expanded in recent years with the increase in energy consumption. Energy is a key input in production and plays a crucial role in the development of an economy. Energy sector interacts with other sectors hence the performances of energy firms are inevitable to follow-up. In the study thirteen energy firms are evaluated with 5 main and 15 sub-criteria for the period of 2008-2013. The 15 sub-criteria are classified in the following main criteria: liquidity, activity, financial leverage, profitability and growth ratios. The weights of the ratios are determined by Fuzzy AHP and then Fuzzy TOPSIS method is used for the rankings of the energy firms. Traditional multi-criteria decision making methods are not used in this study, due to the fact that they are insufficient under uncertainty. After 2008 global financial crisis, the uncertainty has increased all over the world hence the usage of fuzzy methods can provide better results under these conditions. Findings show that Avrasya Oil, Turcas and Aksu have the highest ranking.

  18. 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.

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

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    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.

  20. Parametric Assessment of Water Use Vulnerability Variations Using SWAT and Fuzzy TOPSIS Coupled with Entropy

    OpenAIRE

    Kwangjai Won; Eun-Sung Chung; Sung-Uk Choi

    2015-01-01

    This study assessed the water use vulnerability to include the uncertainty of the weighting values of evaluation criteria and the annual variations of performance values using fuzzy TOPSIS coupled with the Shannon entropy method. This procedure was applied to 12 major basins covering about 88% territory of South Korea. Hydrological components were simulated using Soil and Water Assessment Tool (SWAT) of which parameters were optimally calibrated using SWAT-CUP model. The 15 indicators includ...

  1. 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

  2. Intuitionistic fuzzy entropy and distance measure based TOPSIS method for multi-criteria decision making

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    Deepa Joshi

    2014-07-01

    Full Text Available In this paper, an intuitionistic fuzzy TOPSIS method for multi-criteria decision making (MCDM problem to rank the alternatives is proposed. The proposed method is based on distance measure and intuitionistic fuzzy entropy. The proposed method also uses conversion theorem to convert fuzzy set to intuitionistic fuzzy set given by Jurio et al. (2010. A real case study is taken as an example to find the ranking of four organizations: Bajaj steel, H.D.F.C. bank, Tata steel and Infotech enterprises using real data. In order to compare the different rankingS, they are applied in a portfolio selection problem. Different portfolios are constructed and are analyzed for their risk and return. It is observed that if the portfolios are constructed using the ranking obtained with proposed method, the return is increased with slight increment in risk.

  3. 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.

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

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    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.

  5. Parametric Assessment of Water Use Vulnerability Variations Using SWAT and Fuzzy TOPSIS Coupled with Entropy

    Directory of Open Access Journals (Sweden)

    Kwangjai Won

    2015-08-01

    Full Text Available This study assessed the water use vulnerability to include the uncertainty of the weighting values of evaluation criteria and the annual variations of performance values using fuzzy TOPSIS coupled with the Shannon entropy method. This procedure was applied to 12 major basins covering about 88% territory of South Korea. Hydrological components were simulated using Soil and Water Assessment Tool (SWAT of which parameters were optimally calibrated using SWAT-CUP model. The 15 indicators including hydrological and anthropogenic factors were selected, based on three aspects of climate exposure, sensitivity and adaptive capacity. Their weighting values were objectively quantified using the Entropy method. All performance values of 12 basins obtained from statistic Korea and SWAT simulation were normalized with the consideration of the annual variations from 1991 to 2014 using triangular fuzzy numbers (TFNs. Then, Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS technique was used to quantify the water use vulnerability and rank 12 basins as follows: A12 (Hyeongsan River > A6 (Seomjin River > A5 (Youngsan River > A8 (Mangyung River > A2 (Ansung River > A9 (Dongjin River > A10 (Nakdong River > A3 (Geum River > A4 (Sapgyo River > A11 (Taehwa River > A7 (Tamjin River > A1 (Han River. This framework can be used to determine the spatial priority for sustainable water resources plan and applied to derive the climate change vulnerability on sustainable water resources.

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

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    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.

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

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    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

  8. 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.

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

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    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.

  10. Integrasi Fuzzy AHP-TOPSIS dalam Evaluasi Kualitas Layanan Elektronik Rumah Sakit

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    Ronald Sukwadi

    2014-01-01

    Full Text Available In today’s global era, the electronic service quality (E-SQ development has swept across almost all service sectors. This development represents not only a new paradigm for providing services, but also a weapon for winning competitions. This research aims to examine and determine the key service attributes of E-SQ which is adopted from service quality (SERVQUAL methodology as the reference model. The proposed E-SQ framework will be illustrated with a web service performance example of some public and private hospitals in Indonesia by integrating fuzzy analytic hierarchy process (AHP and technique for order performance by similarity to ideal solution (TOPSIS. Finally, this study shows the implementation of the E-SQ framework in evaluating the complexity of service attributes observed in the hospital healthcare services via websites.

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

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    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.

  12. Induced Interval-Valued Intuitionistic Fuzzy Hybrid Aggregation Operators with TOPSIS Order-Inducing Variables

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    Jun-Ling Zhang

    2012-01-01

    Full Text Available Two induced aggregation operators with novelly designed TOPSIS order-inducing variables are proposed: Induced Interval-valued Intuitionistic Fuzzy Hybrid Averaging (I-IIFHA operator and Induced Interval-valued Intuitionistic Fuzzy Hybrid Geometric (I-IIFHG operator. The merit of two aggregation operators is that they can consider additional preference information of decision maker’s attitudinal characteristics besides argument-dependent information and argument-independent information. Some desirable properties of I-IIFHA and I-IIFHG are studied and theoretical analysis also shows that they can include a wide range of aggregation operators as special cases. Further, we extend these operators to form a novel group decision-making method for selecting the most desirable alternative in multiple attribute multi-interest group decision-making problems with attribute values and decision maker’s interest values taking the form of interval-valued intuitionistic fuzzy numbers, and application research to real estate purchase selection shows its practicality.

  13. 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.

  14. FUZZY-DISTANCE FUNCTION APPROACH FOR MULTIPLE CRITERIA DECISION MAKING

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    Mayank Kumar

    2012-06-01

    Full Text Available In this paper, a method for decision making using fuzzy integral and distance function is presented. Case studies of multiple-response process with correlated responses are used to illustrate the effective application of the proposed approach. The efficacy of this method is compared with the existing methods of MCDM like TOPSIS and GRA. The proposed method is robust, requires less information and less complex as compared to many existing methods.

  15. 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.

  16. 基于模糊 TOPSIS 方法的变压器维修策略%Transformer Maintenance Strategy Based on Fuzzy TOPSIS Method

    Institute of Scientific and Technical Information of China (English)

    张翠玲; 王大志; 宁一; 江雪晨

    2016-01-01

    Transformer maintenance strategy decision is a decision-making problem of hybrid multiple attribute index related to coexistence of quantitative indicators and qualitative indexes. The fuzzy comprehensive evaluation analysis model of the transformer maintenance strategy was set up by using fuzzy TOPSIS,and the decision-making problem of hybrid multiple attribute index was solved.Through calculating the relative closeness degree to determine the transformers operation status,the transformer maintenance strategy could be determined by using the proposed method.In addition,the proposed method not only can monitor transformers operation status,but also can directly determine the best one from various maintenance strategy for a transformer using the expert system .The index values of accurate real type,interval type and fuzzy number were classed and judged,then the relative closeness degree of various maintenance strategy was sorted through analysis and comparison,based on which it could be decided to choose which kind of maintenance strategy.The result of the example shows that the method has good effect on transformer maintenance strategy decision.%变压器维修策略的决策是一种涉及到量化指标和定性分析指标共存的混合多属性指标的决策问题。运用模糊理想解法(fuzzy TOPSIS)建立了变压器维修策略的模糊综合评价分析模型,来解决含有混合多属性指标决策问题。这种方法不仅可以对多台变压器的运行情况进行监视,通过利用计算相对贴近度来确定变压器的运行状态,进而确定变压器的维修策略,而且还可以通过专家系统对1台变压器的多种维修策略进行直接的判断与确定,通过精确的实数型指标值、区间数型的指标值和模糊数的指标值进行分类判断,给出多种维修策略下的取值情况,进而分析比较各个相对贴近度的大小,做出排序,决定选取哪种维修策略。通过实例验证

  17. Evaluation and Ranking of Organizational Resilience Factors by Using a Two-Step Fuzzy AHP and Fuzzy TOPSIS

    Directory of Open Access Journals (Sweden)

    Danijela Tadić

    2014-01-01

    Full Text Available We presented a novel fuzzy multicriteria decision making approach to evaluate and rank organizational resilience factors with respect to user preference orders. Due to vagueness of the decision data, the precise numerical data are inadequate for real-life business situations. Human judgements can be expressed by linguistic expressions which are modeled by fuzzy sets. The complexity of the considered problem calls for analytic methods rather than intuitive decisions. Two fuzzy multi-criteria methods are proposed for solving the treated problem: Fuzzy Analytic Hierarchical Process (FAHP is applied to determine the relative importance of business processes and the relative importance of organizational resilience factors under each business process, and an extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS is applied to rank the organizational resilience factors. With respect to complexity and the type of considered management problem, we introduce a modified fuzzy decision matrix. The proposed algorithm has efficiently been applied in the assessment of organizational resilience factors to small and medium enterprises of the process industry.

  18. Maintainability assessment for software by using a hybrid fuzzy multi-criteria analysis approach

    Directory of Open Access Journals (Sweden)

    Shivani Kundu

    2017-06-01

    Full Text Available Maintainability plays a fundamental role for achieving success in software system and it is con-sidered as an important quality characteristics. Maintainability may be predicted efficiently by us-ing soft computing techniques as they provide good results. In this paper similarity- based ap-proach is used with the contribution of fuzzy Analytical Hierarchical Process (AHP and fuzzy technique for order preference by similarity to ideal solution (TOPSIS at 2-level hierarchy. Here similarity- based approach illustrates the combine approach of fuzzy AHP and fuzzy TOPSIS. This approach is used to provide the rank of software to select the best one for maintainability estimation. Also, several factors are presented that influence the software maintainability. These factors are taken as criterion and three software products are taken as alternatives.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. Supplier Selection for A Textile Company Using The Fuzzy TOPSIS Method(Bir Tekstil Firmasında Bulanık TOPSIS Yöntemiyle Tedarikçi Seçimi

    Directory of Open Access Journals (Sweden)

    V. Sinem ARIKAN KARGI

    2016-12-01

    Full Text Available The rapid changes that occur nowadays increase the uncertainties around companies and make the decision process harder. The problems encountered in real life predominantly have complex structures and depend on multiple criteria and alternatives. For that reason, fuzzy and multiple-criteria decision making methods are gaining importance. The aim of this study is to help a textile company, which produces shirt-making fabric, choose the most suitable yarn supplier from a number of alternatives. To solve the company’s problem in choosing the right supplier, the fuzzy TOPSIS method was proposed in order to handle the linguistic variables used by the decision makers. In the study, the criteria determined by the decision makers were taken into consideration and three suppliers were evaluated to identify the most suitable one

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  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. Approach to fuzzy number intuitionistic fuzzy multi-criteria decision making based on fuzzy structured element%基于模糊结构元的模糊数直觉模糊多准则决策方法

    Institute of Scientific and Technical Information of China (English)

    汪新凡; 王坚强; 杨小娟

    2012-01-01

    A fuzzy structured element method is applied to deal with fuzzy number intuitionistic fuzzy multi-criteria decision making problems with incomplete certain information on criteria's weights. Based on the representation of fuzzy structured element of fuzzy number intuitionistic fuzzy set, the method of fuzzy structured element of fuzzy numbers' comparison and sequencing, and the score function and distance measure of intuitionistic fuzzy numbers, the score function and distance measure of fuzzy number intuitionistic fuzzy numbers are defined. Furthermore, two multi-criteria decision making approaches are proposed, such as the score function method, and the technique for order preference by similarity to ideal solution(TOPSIS) method, in which the criteria values are fuzzy number intuitionistic fuzzy numbers, and the criteria weight information is incompletely certain. Finally, an example is given to show the feasibility and effectiveness of the proposed methods.%针对准则权重信息不完全确定的模糊数直觉模糊多准则决策问题,采用模糊结构元方法进行处理.基于模糊数直觉模糊集的模糊结构元表示、模糊数比较和排序的模糊结构元方法以及直觉模糊数的记分函数和距离测度,定义了模糊数直觉模糊数的记分函数和距离测度,进而提出两种准则权重信息不完全确定而准则值为模糊数直觉模糊数的多准则决策方法:记分函数法和逼近理想解排序(TOPSIS)法.实例分析表明了这两种方法的可行性和有效性.

  7. 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.

  8. 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.

  9. 双极模糊教学质量评价TOPSIS方法%Bipolar Fuzzy Evaluation TOPSIS Method to Teaching Quality

    Institute of Scientific and Technical Information of China (English)

    韩莹; 侯健敏; 毕辉

    2016-01-01

    A bipolar fuzzy TOPSIS evaluation method to teaching quality is introduced in this paper,to solve the shortcoming of existed method that neglects the conflict information.A case is included to illustrate the feasibility of the method in practice.The method benefits to the teaching reform.%针对传统模糊教学评价方法中没有考虑冲突信息的不足,提出了新的基于双极模糊集合的TOPSIS评价方法。实例分析证明了方法在实践中的有效性,对教学评价改革具有一定的意义。

  10. Efficacy of fuzzy MADM approach in Six Sigma analysis phase in automotive sector

    Science.gov (United States)

    Rathi, Rajeev; Khanduja, Dinesh; Sharma, S. K.

    2016-02-01

    Six Sigma is a strategy for achieving process improvement and operational excellence within an organization. Decisions on critical parameter selection in analysis phase are always very crucial; it plays a primary role in successful execution of Six Sigma project and for productivity improvement in manufacturing environment and involves the imprecise, vague and uncertain information. Using a case study approach; the paper demonstrates a tactical approach for selection of critical factors of machine breakdown in center less grinding (CLG) section at an automotive industry using fuzzy logic based multi attribute decision making approach. In this context, we have considered six crucial attributes for selection of critical factors for breakdown. Mean time between failure is found to be the pivotal selection criterion in CLG section. Having calculated the weights pertinent to criteria through two methods (fuzzy VIKOR and fuzzy TOPSIS) critical factors for breakdown are prioritized. Our results are in strong agreement with the perceptions of production and maintenance department of the company.

  11. PRIORITIZING HIGHER EDUCATION BALANCED SCORECARD PERFORMANCE INDICATORS USING FUZZY APPROACH IN AN IRANIAN CONTEXT

    Directory of Open Access Journals (Sweden)

    Daryush Farid

    2008-10-01

    Full Text Available Higher education institutes are facing new challenges in order to improve the quality of education. There is a pressure for restructuring and reforming higher education in order to provide quality education and bring up graduates who become fruitful members of their societies. In higher education as in business there are acceptable conventions of measuring excellence. As a result, the implementation of Balanced Scorecard in higher education has been a target of interest in recent years. However, rather than emphasizing on financial performance, higher education has emphasized on academic measures in its Balanced Scorecard. This paper aims to prioritize performance indicators within the higher education balanced scorecard using fuzzy TOPSIS technique.Because Fuzzy Theory is a better approach in comparison to Logical Theory in case of measuring linguistic terms, therefore this paper tries to apply a fuzzy approach in prioritizing the performance indicators introduced by Balanced Scorecard.

  12. A fuzzy MADM approach for project selection: a six sigma case study

    Directory of Open Access Journals (Sweden)

    Rajeev Rathi

    2016-06-01

    Full Text Available Six Sigma is a strategic approach of significant value in achieving overall excellence. It helps to accomplish the organizations strategic aim through the effectual use of project controlled methodology. As Six Sigma is a project controlled approach, it is necessary to prioritize projects which give utmost economic benefits to the firm. In real practice, Six Sigma projects selection is very tough assignment because poor project selection also happens even in the well-managed organizations and this can weaken the success and trustworthiness of the Six Sigma practice. The present study aims to develop a project selection approach based on a combination of fuzzy and MADM technique to help organizations determine proper Six Sigma projects and identify the priority of these projects mainly in automotive companies. VIKOR and TOPSIS methods have been used to select the proper Six Sigma project composed with fuzzy logic. In this context, seven critical parameters have been considered for selection of finest alternative. The weights of evaluation criteria are obtained using the MDL (modified digital logic method and final ranking is calculated through primacy index obtained by using fuzzy based VIKOR and TOPSIS methodology. A factual case study from automotive industry is used to investigate the efficacy of the planned approach.

  13. 基于模糊TOPSIS的绿色供应链绩效评价%Green supply chain performance evaluation based on fuzzy TOPSIS

    Institute of Scientific and Technical Information of China (English)

    张毕西; 张明珠; 韩正涛

    2014-01-01

    针对绿色供应链管理问题,建立改进的绿色供应链综合绩效评价体系,运用模糊TOPSIS方法构建模糊加权评价矩阵,计算出了各方案与理想解之间的相对贴近度,从而比较不同方案之间的差别,为供应链绩效的评价提供重要决策依据。实证分析验证了该方法的实用性和有效性。%Aiming at the problem of green supply chain management, an improved comprehensive green supply chain performance evaluation system was established, and the fuzzy TOPSIS method was used to build weighted fuzzy evaluation matrix to calculate the relative closeness degree between the programs and the ideal solution , so as to compare the differences between different solutions, and provide important decision basis for the supply chain performance evaluation. Finally, the empirical analysis verified the practicality and effectiveness of the method.

  14. 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.

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Gülşen Akman

    2014-01-01

    Full Text Available 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 solution (TOPSIS method to evaluate and sequence alternatives and to make the final selection. Finally, an actual industrial application is performed in logistics department of a tire manufacturing company. For this, first, eight logistics supplier selection criteria were determined, and then the best alternative among seven logistics service provider companies was selected by the proposed method.

  17. 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.

  18. Developing a Virtual Group Decision Support System Based on Fuzzy Hybrid MCDM Approach

    Directory of Open Access Journals (Sweden)

    Bahram Izadi

    2013-01-01

    Full Text Available Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS. Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Meriastuti - Ginting

    2015-06-01

    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

  1. 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 

  2. Fuzzy differential equations in various approaches

    CERN Document Server

    Gomes, Luciana Takata; Bede, Barnabas

    2015-01-01

    This book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh’s extension. Through a unique analysis, results of all these theories are examined and compared.

  3. 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.

  4. Linear Design Approach to a Fuzzy Controller

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1999-01-01

    A ball-balancer, basically an inverted pendulum problem, is stabilised by a linear controller. With certain design choices, a fuzzy controller is equivalent to a summation; thus it can replace the linear controller. It can be claimed, that the fuzzy controller performs at least as well...... as the linear controller, since the linear controller is contained in the fuzzy controller. The approach makes it somewhat easier to design a fuzzy controller....

  5. 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.

  6. Formulation and categorizing Iran Behnoosh Co. strategies: An Fuzzy approach

    Directory of Open Access Journals (Sweden)

    Hassan. Mehrmanesh

    2012-01-01

    Full Text Available By attention to organization’s growth for competing to achieve more market share, strategic planning necessity has been more and more important for organization the has paid a lot of researchers attention. In this research, firt with refering to accomplished studies, strengths, weaknesses, oppurtunities, treatments and some strategies were distinguished in base of SWOT matrix. Then by defining critical success factors, the strategies were categorized by fuzzy topsis anf QSPM techniques. By the first technique, “producing new goods like water and juice to complete production basket” was chosen as the most important strategy and after that “apply Branding” and “using new production lines in Shirvan and Arak companies to increase productions” were placed in 2nd and 3rd places. Although “apply Branding”, “producing new goods like water and juice to complete production basket” and “allocating a little percentage for healthy drinks marketing” were selected as the top strategies by QSPM technique. Finally fuzzy topsis and QSPM techniques were comprised together by SAW technique. In this stage, 2 mentioned techniques and organization’s long term objectives were considered as althernatives and criterias in direct order that fuzzy topsis was selected as better one for categorizing Behnoosh company strategies.

  7. Investment Portfolio Evaluation by the Fuzzy Approach

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    Lambovska Maya

    2011-09-01

    Full Text Available This paper presents a new fuzzy approach for the evaluation of investment portfolio, where the approach is viewed by the authors as a sub-phase of the management process of these portfolios. The approach defines the mutual and delayed effects among the significant variables of the investment portfolio. The evaluation of the effects is described as fuzzy trapezoidal numbers and they are aggregated by mathematical operations with incidence matrices and fuzzy functions “experton”.

  8. 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.

  9. A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences

    DEFF Research Database (Denmark)

    Shen, Lixin; Olfat, Laya; Govindan, Kannan

    2012-01-01

    protection and the corresponding increase in legislation and regulations, green purchasing has become an important issue for companies to gain environmental sustainability. Traditionally, companies consider criteria such as price, quality and lead time, when evaluating supplier performance and do not give...... enough attention to environmental criteria as a means to evaluate suppliers. Now, many companies have begun to implement green supply chain management (GSCM) and to consider environmental issues and the measurement of their suppliers' environmental performance. This paper examines GSCM to propose a fuzzy...... multi criteria approach for green suppliers' evaluation. We apply fuzzy set theory to translate the subjective human perceptions into a solid crisp value. These linguistic preferences are combined through fuzzy TOPSIS to generate an overall performance score for each supplier. A numerical example...

  10. 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.

  11. 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.

  12. A Hybrid Fuzzy Analytic Network Process Approach to the New Product Development Selection Problem

    Directory of Open Access Journals (Sweden)

    Chiuh-Cheng Chyu

    2014-01-01

    Full Text Available New product development selection is a complex decision-making process. To uphold their competence in competitive business environments, enterprises are required to continuously introduce novel products into markets. This paper presents a fuzzy analytic network process (FANP for solving the product development selection problem. The fuzzy set theory is adopted to represent ambiguities and vagueness involved in each expert’s judgment. In the proposed model, the fuzzy Kano method and fuzzy DEMATEL are employed to filter criteria and establish interactions among the criteria, whereas the SAM is applied to aggregate experts’ opinions. Unlike the commonly used top-down relation-structuring approach, the proposed FANP first identifies the interdependence among the criteria and then the identified relationships are mapped to the clusters. This approach is more realistic, since the inner and outer relationships between criteria are simultaneously considered to establish the relationships among clusters. The proposed model is illustrated through a real life example, with a comparative analysis using modified TOPSIS and gray relation analysis in the synthesizing phase. The concluded results were approved by the case company. The proposed methodology not only is useful in the case study, but also can be generally applied in other similar decision situations.

  13. Evaluation of Fuzzy Pareto Solution Set by Using Fuzzy Relation Based Clustering Approach For Fuzzy Multi-Response Experiments

    Directory of Open Access Journals (Sweden)

    Özlem Türkşen

    2013-01-01

    Full Text Available The solution set of a multi-response experiment is characterized by Pareto solution set. In this paper, the multi-response experiment is dealed in a fuzzy framework. The responses and model parameters are considered as triangular fuzzy numbers which indicate the uncertainty of the data set. Fuzzy least square approach and fuzzy modified NSGA-II (FNSGA-II are used for modeling and optimization, respectively. The obtained fuzzy Pareto solution set is grouped by using fuzzy relational clustering approach. Therefore, it could be easier to choose the alternative solutions to make better decision. A fuzzy response valued real data set is used as an application.

  14. Ranking of Companies based on TOPSIS-DEA Approach Methods (Case Study of Cement Industry in Tehran Stock Exchange

    Directory of Open Access Journals (Sweden)

    Ali Mansory

    2014-08-01

    Full Text Available Ranking options has always been the main issue for managers. There are a lot of qualitative and quantitative approaches for ranking. However most of the approaches for separating and ranking corporations in stock market are less reliable and the results obtained will be invalid. While the evaluation obtained merely through qualitative or quantitative approaches alone, the advantages of integration will be ignored. Thus logically the efficiency of result will be questionable. Thus in this paper the advantages of qualitative and quantitative approaches are integrated which in turn bring about more precision in values of input and output indices. Hence in this paper the approaches, TOPSIS & DEA, have been introduced to rate active companies in cement industry accepted in Tehran stock market. The approach adopted in this paper is applicable and carried out during 2006-2011 and the population of the research includes accepted companies in stock market in cement industry (28 companies and at the end a precise ranking of the companies is presented by integrattive techniques.

  15. 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.

  16. 三角模糊数的TOPSIS评价方法在弹药运输路径优选中的应用%Application of TOPSIS Evaluation Methodology in Ammo Transportation Route Optimization Based on Triangular Fuzzy Number

    Institute of Scientific and Technical Information of China (English)

    孙丽君

    2013-01-01

    Wartime ammo transportation route selection and evaluation is a process of multi-objective decision. In order to select and evaluate the ammo transportation route systematic and scientifically,a target system was structured compounded by haulage time,safety and guarantee price. The TOPSIS evaluation methodology based on triangular fuzzy number was used to evaluate the selection of ammo transportation route. Result shows that,evaluate method of triangular fuzzy number based TOPSIS is suitable for wartime ammo transportation route selection and can provide scientific basis of army ammo guarantee.%战时弹药运输的路径选择评价是一个多属性决策过程,为了对弹药运输的路径进行系统科学地评价和选择,构建由运输时间、安全性和保障代价3个评价指标组成的指标体系,运用三角模糊数的TOPSIS评价方法,对弹药运输线路的选择进行了实证分析评价。分析结果表明:三角模糊数的TOPSIS评价方法对战时弹药运输的路径选择有较好的适用性,能有效为部队的弹药保障工作提供科学依据。

  17. A new tool for assessing sediment quality based on the Weight of Evidence approach and grey TOPSIS.

    Science.gov (United States)

    Jiang, Yu-Xia; Liu, You-Sheng; Ying, Guang-Guo; Wang, Hong-Wei; Liang, Yan-Qiu; Chen, Xiao-Wen

    2015-12-15

    Sediment is an important part of an aquatic ecosystem, so it is essential to develop an effective sediment quality assessment tool. This study aims to develop a new sediment quality assessment tool using a Weight of Evidence approach in combination with the grey TOPSIS (Technique for Order Preference by Similarity, a mathematical calculation of multi-criteria decision analysis). This tool can analyze data from chemical analyses, laboratory toxicity tests and benthic community structure analyses to generate individual results from each line of evidence, and integrate data from these three lines of evidence to obtain an overall assessment through an Excel Visual Basic for Application program. The tool can compare the relative magnitude of risks among sites and rate each site with high, moderate, or low ecological risk, thus guiding us to take pertinent measures toward polluted sediment. A case study of the sediment of Dongjiang River basin, south China, demonstrated the successful application of this tool. It proved that this assessment tool can provide a comprehensive and accurate assessment of sediment quality and efficiently discriminate risks among different sites, suggesting it is a powerful tool for environment risk assessment.

  18. 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.

  19. Evaluation of High-Tech Research Project Based on Internal Fuzzy TOPSIS and AHP%基于AHP和区间模糊TOPSIS法的高新技术科研项目评价

    Institute of Scientific and Technical Information of China (English)

    张守华; 孙树栋

    2011-01-01

    An evaluation index system of high-tech research project was established, and the evaluation model for high-tech research project was put forward based on analytical hierachy process (AHP) and internal fuzzy technique order preference by similarity to an ideal solution (TOPSIS). And the weight of evaluation index was made using AHP, the interval fuzzy matrix was set using fuzzy theory. The positive ideal solution, negative ideal solution and proximity were calculated. The rank of high-tech research project was made by comparing the proximity. At last, an example was discussed to validate the practicability and feasibility of the established index system and model.%建立了高新技术科研项目评价指标体系,提出了基于层次分析法(AHP)和区间模糊的逼近理想排序法的高新技术科研项目评价模型,采用AHP确定评价指标的权重,借助于模糊理论构建区间模糊矩阵,计算其正、负理想解和接近度,根据接近度而对高新技术科研项目进行比较,并进行了实例分析.结果表明,所构建的评价指标体系和评价模型具有一定的实用性和可行性.

  20. Application of Fuzzy TOPSIS Based on alpha Level Sets in Evaluating Public Crisis Management Capability%基于α-水平截集的模糊 TOPSIS 方法在公共危机管理能力评价中的应用研究

    Institute of Scientific and Technical Information of China (English)

    于丽英; 蒋宗彩

    2013-01-01

    科学、客观地评价公共危机管理能力,对于完善危机管理系统有着重要的意义。本文从危机前预警能力,危机中处理能力和危机后恢复能力三个维度构建了公共危机管理能力评价指标体系。考虑到人们对复杂事物判断的模糊性,采用三角模糊数将专家给出的定性评价结果量化,结合α-水平截集和TOPSIS建立了公共危机管理能力综合评价模型,并通过求解非线性规划问题得出危机管理能力的模糊相对贴近度,进而去模糊化得出评价结果。最后用该模型对公共危机管理能力进行实证分析,验证了该模型的可行性和有效性。%Scientific and objective evaluation of public crisis management is of vital importance to the improve-ment of crisis management system .A three-perspective evaluation system of crisis management capability is pro-posed in this paper , which includes the forecast capability before crisis , emergency response capability during crisis, and recovery capability after crisis .Considering the ambiguity of people ’ s judgment about complex things , the triangular fuzzy numbers are used to quantize experts ’ qualitative evaluation results .A fuzzy TOPSIS evaluation model based on alpha level sets and a nonlinear programming ( NLP) solution procedure to acquire the fuzzy relative closeness of each alternative are put forward to get the objective evaluation result without fuzziness . A case study is carried out to testify the feasibility and effectiveness of the model .

  1. 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.

  2. Fuzzy Similarity in Multicriteria Decision-Making Problem Applied to Supplier Evaluation and Selection in Supply Chain Management

    Directory of Open Access Journals (Sweden)

    Pasi Luukka

    2011-01-01

    Full Text Available It is proposed to use fuzzy similarity in fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. According to the concept of fuzzy TOPSIS earlier methods use closeness coefficient which is defined to determine the ranking order of all suppliers by calculating the distances to both fuzzy positive-ideal solution (FPIS and fuzzy negative-ideal solution (FNIS simultaneously. In this paper we propose a new method by doing the ranking using similarity. New proposed method can do ranking with less computations than original fuzzy TOPSIS. We also propose three different cases for selection of FPIS and FNIS and compare closeness coefficient criteria and fuzzy similarity criteria. Numerical example is used to demonstrate the process. Results show that the proposed model is well suited for multiple criteria decision-making for supplier selection. In this paper we also show that the evaluation of the supplier using traditional fuzzy TOPSIS depends highly on FPIS and FNIS, and one needs to select suitable fuzzy ideal solution to get reasonable evaluation.

  3. 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.

  4. An Efficient Approach for Fuzzy Project Network Analysis

    Institute of Scientific and Technical Information of China (English)

    HU Jing-song

    2002-01-01

    In this paper we present two-level linear programming method for determining latest dates and slack times in project network models with triangular fuzzy number or trapezoidal fuzzy number. Compared with the well-known fuzzy network techniques in literature, the approach always produces the meaningful latest dates and slack times. Practically we have generalized critical path method by accepting imprecise,fuzzy data for the duration of the activities.

  5. A taxonomy fuzzy filtering approach

    Directory of Open Access Journals (Sweden)

    Vrettos S.

    2003-01-01

    Full Text Available Our work proposes the use of topic taxonomies as part of a filtering language. Given a taxonomy, a classifier is trained for each one of its topics. The user is able to formulate logical rules combining the available topics, e.g. (Topic1 AND Topic2 OR Topic3, in order to filter related documents in a stream. Using the trained classifiers, every document in the stream is assigned a belief value of belonging to the topics of the filter. These belief values are then aggregated using logical operators to yield the belief to the filter. In our study, Support Vector Machines and Naïve Bayes classifiers were used to provide topic probabilities. Aggregation of topic probabilities based on fuzzy logic operators was found to improve filtering performance on the Renters text corpus, as compared to the use of their Boolean counterparts. Finally, we deployed a filtering system on the web using a sample taxonomy of the Open Directory Project.

  6. 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 ...

  7. 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.

  8. Encoding spatial images: A fuzzy set theory approach

    Science.gov (United States)

    Sztandera, Leszek M.

    1992-01-01

    As the use of fuzzy set theory continues to grow, there is an increased need for methodologies and formalisms to manipulate obtained fuzzy subsets. Concepts involving relative position of fuzzy patterns are acknowledged as being of high importance in many areas. In this paper, we present an approach based on the concept of dominance in fuzzy set theory for modelling relative positions among fuzzy subsets of a plane. In particular, we define the following spatial relations: to the left (right), in front of, behind, above, below, near, far from, and touching. This concept has been implemented to define spatial relationships among fuzzy subsets of the image plane. Spatial relationships based on fuzzy set theory, coupled with a fuzzy segmentation, should therefore yield realistic results in scene understanding.

  9. Selection of Urban Temporary Shelter Based on Fuzzy-set Theory and TOPSIS Method%基于模糊集值理论和TOPSIS法的应急避难所选择研究

    Institute of Scientific and Technical Information of China (English)

    宋伟程

    2014-01-01

    针对城市突发事件下人员疏散应急避难所的选择,从安全性、可达性、应急服务能力三个方面构建评价指标体系。考虑到评价指标的不确定性,采用指标区间评分和模糊集值统计理论确定评价指标权重值,利用 TOPSIS 法原理构建应急避难所选择综合评价模型,确定各评价指标的最优解与最劣解,通过计算各评价指标到最优解和最劣解的距离得到各备选应急避难所与最优解的接近程度,按照接近程度对各应急避难所进行排序。实例计算结果表明:到危险源距离、避难所容量、到医院距离、到救援物质仓库距离是避难所选择的主要因素,到最优解距离越小,接近程度越大,该应急避难所越优。%For evacuation shelter choosing under emergency event in a city, an evaluation index system was established from the view points of safety, accessibility and emergency service capabilities. Considering the uncertainty of these evaluation indexes, and combined with the interval marking for each index with the theory of fuzzy set-valued statistics the evaluation index weight was determined. Then, a comprehensive evaluation model of emergency shelter choosing was constructed based on the TOPSIS method, and the optimal solution and the worst solution of each index were obtained. The distances between each alternative shelter and the optimal solution were obtained by calculated the distances from each index to the optimal solution and the worst solution. Each alternative shelter was sorted according to the distances. The greater the distance was, the better the alternative shelter would be. An example showed that: the distances to the hazardous point, to the hospital, to the rescue material warehouse and the capacity of shelter were the main factors for a temporary shelter choosing. If the distance to the optimal solution was samller and the distance was shorter, the emergency shelter would be

  10. Runway Incursion Risk Assessment Based on Fuzzy Sets Theory and Improved TOPSIS Method%基于模糊集和改进TOPSIS方法的跑道侵入风险评估

    Institute of Scientific and Technical Information of China (English)

    罗军; 林雪宁

    2012-01-01

    为预防民航机场跑道侵入事件的发生,减轻塔台管制员面临的跑道运行安全的压力,根据国际民航组织(ICAO)颁布的《防止跑道侵入手册》描述的空中交通管制(ATC)因素,建立影响跑道侵入的ATC指标评价体系.首先运用模糊集理论建立评价模型,并计算子指标的模糊可能性值,其值反映所论子指标风险概率.其次,采用改进的TOPSIS方法进行验证,并计算子指标的信度效度值.结果表明,得出的子指标风险值与模糊可能性值的排序一致.最后,根据子指标风险值的大小提出防止跑道侵入事件发生的建议.%In order to prevent civil aviation airport' s runway incursion accidents and reduce the pressure on the tower controllers, which comes from civil aviation airport' s runway safety operation, an ATC evaluation system of indexes influencing runway incursion was established, according to the control traffic control factors described in the Manual on the Prevention of Runway Incursions published by ICAO. Firstly, an evalution model was built using fuzzy set theory. Fuzzy probability values of subindexes were calculated, these values each reflect the risk of each subindex. Secondly, the reliability and validity values of subindexes were calculated using improved TOPSIS metod. The results show that there is no diference between the sequence of the risk probabilities of subindexes and that of their fuzzy probabilities. Lastly, recommendations for preventing runway incursion accidents were put forward.

  11. 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.

  12. 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.

  13. Fuzzy evaluation method using fuzzy rule approach in multicriteria analysis

    Directory of Open Access Journals (Sweden)

    Othman Mahmod

    2008-01-01

    Full Text Available A multicriteria analysis in ranking the quality of teaching using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the quality of teaching in several courses. The proposed method introduces normalizing data which dampen the extreme value that exists in the data. The use of the model is suitable in evaluating situations that involve subjectivity, vagueness and imprecise information. Experimental results are comparable and the method performs better in some domains. .

  14. Risk Evaluation of Wartime Equipment Supply Chain Based on TOPSIS Method with Fuzzy Ameliorated Entropy Weight%基于模糊修正熵权TOPSIS的战时装备供应链风险评估

    Institute of Scientific and Technical Information of China (English)

    王天虹; 宋业新; 宋长青

    2012-01-01

    According to the characteristics of wartime equip supply chain, long-distance exactitude stroke, enemy raid in rear and influence of bad weather are used to reflect main risk criteria. Based on TOPSIS method with fuzzy ameliorated entropy weight is erected to evaluate the wartime equip supply chain's risk evaluation. Firstly, entropy weight that originated from original data is put forward, which is ameliorated by the experts' factor, and an evaluation method of technique for order preference by similarity to ideal solution is constructed. Finally, the calculation and analysis of an example indicate that this method is easy in calculation, the outcome is reasonable, the subjectivity and randomicity in the commander's decision process are decreased.%针对战时装备供应链的特点,以远程精确打击、敌特后方袭扰和恶劣天气等三个因素为主要风险指标,运用修正的模糊信息熵权对TOPSIS法进行改进,提出了一种新的战时装备供应链风险评估方法.首先利用原始数据产生的模糊信息熵权进行客观赋权,并引入专家因素对权重进行主观修正,利用逼近理想解排序方法进行运算,最后通过实例计算与分析,验证该评估方法简便易行,结论合理,有效降低了指挥员决策的主观随意性.

  15. 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;

  16. Applying a Hybrid QFD-TOPSIS Method to Design Product in the Industry (Case Study in Sum Service Company

    Directory of Open Access Journals (Sweden)

    Babak Haji Karimi

    2012-09-01

    Full Text Available Electronics industry as an industry with high added value and television production industry especially as one of its pillars play an important role in the economy of each country. Therefore, the aim study of this paper is to illustrate how, using a combined QFD-TOPSIS model, organizations are able to their design product in accordance with requirements of consumers with a case study in Sum Service Company. Quality Function Deployment (QFD is one such extremely important quality management tool that is useful in product design and development. Traditionally, QFD rates the Design Requirements (DRs with respect to customer needs 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 is variety of 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 fuzzy QFDTOPSIS methodology was applied for the Sum Service Company in Iran.

  17. An Interactive Decomposition Algorithm for Two-Level Large Scale Linear Multiobjective Optimization Problems with Stochastic Parameters Using TOPSIS Method

    Directory of Open Access Journals (Sweden)

    Tarek H. M. Abou-El-Enien

    2015-04-01

    Full Text Available This paper extended TOPSIS (Technique for Order Preference by Similarity Ideal Solution method for solving Two-Level Large Scale Linear Multiobjective Optimization Problems with Stochastic Parameters in the righthand side of the constraints (TL-LSLMOP-SPrhs of block angular structure. In order to obtain a compromise ( satisfactory solution to the (TL-LSLMOP-SPrhs of block angular structure using the proposed TOPSIS method, a modified formulas for the distance function from the positive ideal solution (PIS and the distance function from the negative ideal solution (NIS are proposed and modeled to include all the objective functions of the two levels. In every level, as the measure of ―Closeness‖ dp-metric is used, a k-dimensional objective space is reduced to two –dimentional objective space by a first-order compromise procedure. The membership functions of fuzzy set theory is used to represent the satisfaction level for both criteria. A single-objective programming problem is obtained by using the max-min operator for the second –order compromise operaion. A decomposition algorithm for generating a compromise ( satisfactory solution through TOPSIS approach is provided where the first level decision maker (FLDM is asked to specify the relative importance of the objectives. Finally, an illustrative numerical example is given to clarify the main results developed in the paper.

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

    Science.gov (United States)

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    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.

  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. Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

    Science.gov (United States)

    Indarsih, Indrati, Ch. Rini

    2016-02-01

    In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

  2. Fuzzy linear programming approach for solving transportation problems with interval-valued trapezoidal fuzzy numbers

    Indian Academy of Sciences (India)

    ALI EBRAHIMNEJAD

    2016-03-01

    Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at destinations using available supplies at origins in a crisp environment. In real life situations, the decision maker may not be sure about the precise values of the coefficients belonging to the transportation problem. The aim of this paper is to introduce a formulation of TP involving interval-valued trapezoidal fuzzy numbers for the transportation costs and values of supplies and demands. We propose a fuzzy linear programming approach for solvinginterval-valued trapezoidal fuzzy numbers transportation problem based on comparison of interval-valued fuzzy numbers by the help of signed distance ranking. To illustrate the proposed approach an application example issolved. It is demonstrated that study of interval-valued trapezoidal fuzzy numbers transportation problem gives rise to the same expected results as those obtained for TP with trapezoidal fuzzy numbers.

  3. Fuzzy Document Clustering Approach using WordNet Lexical Categories

    Science.gov (United States)

    Gharib, Tarek F.; Fouad, Mohammed M.; Aref, Mostafa M.

    Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. This area is growing rapidly mainly because of the strong need for analysing the huge and large amount of textual data that reside on internal file systems and the Web. Text document clustering provides an effective navigation mechanism to organize this large amount of data by grouping their documents into a small number of meaningful classes. In this paper we proposed a fuzzy text document clustering approach using WordNet lexical categories and Fuzzy c-Means algorithm. Some experiments are performed to compare efficiency of the proposed approach with the recently reported approaches. Experimental results show that Fuzzy clustering leads to great performance results. Fuzzy c-means algorithm overcomes other classical clustering algorithms like k-means and bisecting k-means in both clustering quality and running time efficiency.

  4. Allocation of CNG Stations in Urban Street Networks Based on GIS Approach and Prioritization with AHP and Topsis Methods (Case Study: Rasht City

    Directory of Open Access Journals (Sweden)

    Ali Abdi

    2013-04-01

    Full Text Available Today’s finding a proper location of transport services widely contributes to the organization of city street networks. Fuel refueling station networks include urban services acted as urban transport supply and it accounts in terms of traffic considerations, urbanization, security and environment. In this study, with respect to CNG refuel stations and criteria for proposed guidelines some variables are the following: Land¬ uses, Traffic networks, population, traffic volume, infrastructure facilities, acces¬ses. Then using a Arc Map software, resources map and limiting factors to Rasht city have been overlapped and locations have been proposed. In the next stage questionnaires have been arranged in the form of pair comparisons and bipolar scales besides variables were given relative weights by experts. Afterwards, for choosing the best place, an approach called AHP in the form of Expert Choice to determine the ultimate weight of variables and spaces. Traffic volume with 34.3% and infrastructure facilities 33.4% ranked first and second respectively. Place No.8 ranked first with 19.2%. Besides to grade, criterions are scored in the form of TOPSIS using bipolar their weight determine¬d by entropy. The most weight is with the infrastructure facilities variables at the rate of 30.9%. Then proposed places have been ranked. Place No.7 ranked first with 0.766. In the end priority order are compared and AHP is selected for ranking.

  5. Evaluation of remedial options for a benzene-contaminated site through a simulation-based fuzzy-MCDA approach.

    Science.gov (United States)

    Yang, A L; Huang, G H; Qin, X S; Fan, Y R

    2012-04-30

    A simulation-based fuzzy multi-criteria decision analysis (SFMCDA) method is developed for supporting the selection of remediation strategies for petroleum contaminated sites. SFMCDA integrates process modeling (using BIOPLUME III) and fuzzy ranking (based on fuzzy TOPSIS) into a general management framework, and can compare various remediation alternatives, in light of both cost-risk tradeoffs and uncertainty impacts. The proposed method is applied to a hypothetical contaminated site suffering from a benzene leakage problem. Six remediation alternatives are taken into consideration, including natural attenuation (NA), pump-and-treat (PAT), enhanced natural attenuation (ENA), and a number of their combinations. Six fuzzy criteria, including both cost and risk information, are used to compare different alternatives through fuzzy TOPSIS. The results demonstrates that the proposed method can help systematically analyze fuzzy inputs from contaminant transport modeling, cost implications and stakeholders' preferences, and provide useful ranking information covering a variety of decision-relevant remediation options for decision makers. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

  6. The Fuzzy Sets Approach to Pattern Recognition

    Science.gov (United States)

    Wilson, T.

    1972-01-01

    The fuzzy set concept is defined and its application to pattern recognition is illustrated. An iterative procedure for learning the equi-membership surfaces and for generating a set of discriminate functions for two pattern classes is given.

  7. RISK BASED TESTING A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Ochin Sharma

    2011-10-01

    Full Text Available Earlier Testers used to concentrate on only functionality, usability or performance sort of testing. Many of these derived by the customer’s desire or need. Same thing was with the risk based testing. If an application used to be real time based or crucial in terms or national security or economic then it was considered to be a risk based testing candidate. But business of individual has equalimportance for the people. Hence now risked based scenario and testing is a must do strategy. But based on the various factors how will you decide when an event or activity is under risk and should be treated on priority based. In real time projects many activities cannot be decided as ‘Yes’ or ‘No’ criteria. For example in a project if any one person is left out of 10 members’ team. It cannot be treated as crucial, but if 5 members left within short span of time. This 50% breakdown in work force definitely be consider as critical, so here we can wave a red (priority signal. So fuzzy approach can be consider as an important deal with respect of risk management

  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. Pressure Vessel Optimization a Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Mr. Uday V. Aswalekar

    2015-05-01

    Full Text Available Optimization has become a significant area of development, both in research and for practicing design engineers. In this work here for optimization of air receiver tank, of reciprocating air compressor, the sequential linear programming method is being used. The capacity of tank is considered as optimization constraint. Conventional dimension of the tank are utilized as reference for defining range. Inequality constraints such as different design stresses for different parts of tank are determined and suitable values are selected. Algorithm is prepared and conventional SLP is done in MATLAB Software with C++ interface toget optimized dimension of tank. The conventional SLP is modified by introducing fuzzy heuristics and the relevant algorithm is prepared. Fuzzy based sequential linear programming is prepared and executed in MATLAB Software using fuzzy toolbox and optimization tool box and corresponding dimension are obtained. After comparison FSLP with SLP it is observed that FSLP is easier in execution.

  10. A Fuzzy Approach to Classify Learning Disability

    Directory of Open Access Journals (Sweden)

    Pooja Manghirmalani

    2012-05-01

    Full Text Available 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 into its various types. This expert system facilitates in simulating conditions which are otherwise imprecisely defined.

  11. Fuzzy Array Approach to Unit Commitment

    DEFF Research Database (Denmark)

    Jantzen, Jan; Eliasson, Bo

    1996-01-01

    The paper investigates the unit commitment problem of Swedish power company Sydkraft as a constraint satisfaction problem. The power system is a simplified system with nuclear, thermal, and hydro generators as well as power interchange. In this paper we focus on soft constraints, for instance `ap...... `approximately equal`, `much larger than`, and `a little`. Several authors have recognized the significance of soft or fuzzy constraints. Our specific objective is to compute a power balance by means of fuzzy array logic in order to accommodate uncertainty....

  12. Analysis of Kernel Approach in Fuzzy-Based Image Classifications

    Directory of Open Access Journals (Sweden)

    Mragank Singhal

    2013-03-01

    Full Text Available This paper presents a framework of kernel approach in the field of fuzzy based image classification in remote sensing. The goal of image classification is to separate images according to their visual content into two or more disjoint classes. Fuzzy logic is relatively young theory. Major advantage of this theory is that it allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. This paper describes how remote sensing data with uncertainty are handled with fuzzy based classification using Kernel approach for land use/land cover maps generation. The introduction to fuzzification using Kernel approach provides the basis for the development of more robust approaches to the remote sensing classification problem. The kernel explicitly defines a similarity measure between two samples and implicitly represents the mapping of the input space to the feature space.

  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. Fuzzy Set Theoretical Approach to Document Retrieval.

    Science.gov (United States)

    Radecki, Tadeusz

    1979-01-01

    Presents a new method of document retrieval based on the fundamental operations of fuzzy set theory. Basic notions are introduced. Then the syntax and semantics of the proposed language for document retrieval is given, and an algorithm allocating documents to particular queries is described and its properties are discussed. (Author/CWM)

  15. Discovering Fuzzy Censored Classification Rules (Fccrs: A Genetic Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Renu Bala

    2012-08-01

    Full Text Available Classification Rules (CRs are often discovered in the form of ‘If-Then’ Production Rules (PRs. PRs, beinghigh level symbolic rules, are comprehensible and easy to implement. However, they are not capable ofdealing with cognitive uncertainties like vagueness and ambiguity imperative to real word decision makingsituations. Fuzzy Classification Rules (FCRs based on fuzzy logic provide a framework for a flexiblehuman like reasoning involving linguistic variables. Moreover, a classification system consisting of simple‘If-Then’ rules is not competent in handling exceptional circumstances. In this paper, we propose aGenetic Algorithm approach to discover Fuzzy Censored Classification Rules (FCCRs. A FCCR is aFuzzy Classification Rule (FCRs augmented with censors. Here, censors are exceptional conditions inwhich the behaviour of a rule gets modified. The proposed algorithm works in two phases. In the firstphase, the Genetic Algorithm discovers Fuzzy Classification Rules. Subsequently, these FuzzyClassification Rules are mutated to produce FCCRs in the second phase. The appropriate encodingscheme, fitness function and genetic operators are designed for the discovery of FCCRs. The proposedapproach for discovering FCCRs is then illustrated on a synthetic dataset.

  16. 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.

  17. A TWO-PHASE APPROACH TO FUZZY SYSTEM IDENTIFICATION

    Institute of Scientific and Technical Information of China (English)

    Ta-Wei HUNG; Shu-Cherng FANG; Henry L.W.NUTTLE

    2003-01-01

    A two-phase approach to fuzzy system identification is proposed. The first phase produces a baseline design to identify a prototype fuzzy system for a target system from a coIlection of input-output data pairs. It uses two easily implemented clustering techniques: the subtractive clustering method and the fuzzy c-means (FCM) clustering algorithm. The second phase (fine tuning)is executed to adjust the parameters identified in the baseline design. This phase uses the steepest descent and recursive least-squares estimation methods. The proposed approach is validated by applying it to both a function approximation type of problem and a classification type of problem. An analysis of the learning behavior of the proposed approach for the two test problems is conducted for further confirmation.

  18. Guiding Mobile Robot by Applying Fuzzy Approach on Sonar Sensors

    Directory of Open Access Journals (Sweden)

    Ahmed Rahman Jasim

    2010-01-01

    Full Text Available This study describes how fuzzy logic control FLC can be applied to sonars of mobile robot. The fuzzy logic approach has effects on the navigation of mobile robots in a partially known environment that are used in different industrial and society applications. The fuzzy logic provides a mechanism for combining sensor data from all sonar sensors which present different information. The FLC approach is achieved by means of Fuzzy Decision Making method type of fuzzy logic controller. The proposed controller is responsible for the obstacle avoidance of the mobile robot while traveling through a map from a home point to a goal point. The FLC is built as a subprogram based on the intelligent architecture (IA. The software program uses the Advanced Robotics Interface for Applications (ARIA, it is programmed with C++ package ( Visual C++.Net , and Networking software is used for setup Wireless TCP/IP Ethernet-to-Serial connection between robot and PC. The results show that the developed mobile robot travels successfully from one location to another and reaches its goal after avoiding all obstacles that are located in its way. The platform mobile robot is a Pioneer 3 DX that is equipped with Sonar sensors.

  19. Delay Computation Using Fuzzy Logic Approach

    Directory of Open Access Journals (Sweden)

    Ramasesh G. R.

    2012-10-01

    Full Text Available The paper presents practical application of fuzzy sets and system theory in predicting delay, with reasonable accuracy, a wide range of factors pertaining to construction projects. In this paper we shall use fuzzy logic to predict delays on account of Delayed supplies and Labor shortage. It is observed that the project scheduling software use either deterministic method or probabilistic method for computation of schedule durations, delays, lags and other parameters. In other words, these methods use only quantitative inputs leaving-out the qualitative aspects associated with individual activity of work. The qualitative aspect viz., the expertise of the mason or the lack of experience can have a significant impact on the assessed duration. Such qualitative aspects do not find adequate representation in the Project Scheduling software. A realistic project is considered for which a PERT chart has been prepared using showing all the major activities in reasonable detail. This project has been periodically updated until its completion. It is observed that some of the activities are delayed due to extraneous factors resulting in the overall delay of the project. The software has the capability to calculate the overall delay through CPM (Critical Path Method when each of the activity-delays is reported. We shall now demonstrate that by using fuzzy logic, these delays could have been predicted well in advance.

  20. 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.

  1. 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

  2. Probabilistic Fuzzy Approach to Evaluation of Logistics Service Effectiveness

    Directory of Open Access Journals (Sweden)

    Rudnik Katarzyna

    2014-12-01

    Full Text Available Logistics service providers offer a whole or partial logistics business service over a certain time period. Between such companies, the effectiveness of specific logistics services can vary. Logistics service providers seek the effective performance of logistics service. The purpose of this paper is to present a new approach for the evaluation of logistics service effectiveness, along with a specific computer system implementing the proposed approach – a sophisticated inference system, an extension of the Mamdani probabilistic fuzzy system. The paper presents specific knowledge concerning the relationships between effectiveness indicators in the form of fuzzy rules which contain marginal and conditional probabilities of fuzzy events. An inference diagram is also shown. A family of Yager's parameterized t-norms is proposed as inference operators. It facilitates the optimization of system parameters and enables flexible adjustment of the system to empirical data. A case study was used to illustrate the new approach for the evaluation of logistics service effectiveness. The approach is demonstrated on logistics services in a logistics company. We deem the analysis of a probabilistic fuzzy knowledge base to be useful for the evaluation of effectiveness of logistics services in a logistics company over a given time period.

  3. A fuzzy approach to the Weighted Overlap Dominance model

    DEFF Research Database (Denmark)

    Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt

    2013-01-01

    in an interactive way, where input data can take the form of uniquely-graded or interval-valued information. Here we explore the Weighted Overlap Dominance (WOD) model from a fuzzy perspective and its outranking approach to decision support and multidimensional interval analysis. Firstly, imprecision measures...

  4. 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.

  5. Maximum entropy approach to fuzzy control

    Science.gov (United States)

    Ramer, Arthur; Kreinovich, Vladik YA.

    1992-01-01

    For the same expert knowledge, if one uses different &- and V-operations in a fuzzy control methodology, one ends up with different control strategies. Each choice of these operations restricts the set of possible control strategies. Since a wrong choice can lead to a low quality control, it is reasonable to try to loose as few possibilities as possible. This idea is formalized and it is shown that it leads to the choice of min(a + b,1) for V and min(a,b) for &. This choice was tried on NASA Shuttle simulator; it leads to a maximally stable control.

  6. 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).

  7. Development and Optimization of Hybrid Friction Materials Consisting of Nanoclay and Carbon Nanotubes by using Analytical Hierarchy Process (AHP and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS under Fuzzy Atmosphere

    Directory of Open Access Journals (Sweden)

    Tej SINGH

    2013-07-01

    Full Text Available The tribo-performance of nanoclay and multi-walled carbon nanotube (MWNT filled and graphite lubricated phenolic composites, reinforced with a combination of lapinus and kevlar fibers, have been evaluated on a Kraus friction testing machine. The combined fuzzy analytical hierarchy process (FAHP and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS approach, taking into account performance defining attributes (PDAs such as friction performance, wear, friction-fade, friction-recovery, stability coefficient, variability coefficient, friction fluctuations and temperature rise of the disc, was used for the performance assessment of fabricated friction composite materials. The weight of different PDAs were evaluated by FAHP; μ-performance (0.144, 0.255, 0.435, wear (0.144, 0.255, 0.435, fade-% (0.073, 0.15, 0.307, recovery-% (0.063, 0.126, 0.268, stability coefficient (0.037, 0.075, 0.156, variability coefficient (0.032, 0.063, 0.136, frictional fluctuations (0.023, 0.037, 0.069, and DTR (0.023, 0.037, 0.069 respectively.  FTOPSIS was employed to determine the optimal ranking of the friction composite materials as NC-7>NC-8>NC-6>NC-5>NC-3>NC-4>NC-2>NC-1. The alternative with kevlar: lapinus, 2.5:27.5 wt-% and graphite: nanoclay: carbon nanotube, 2.25:2.75 wt-% exhibits the optimal properties.

  8. A fuzzy pert approach to evaluate plant construction project scheduling risk under uncertain resources capacity

    Directory of Open Access Journals (Sweden)

    Hsian Jong Hsiau

    2009-07-01

    Full Text Available A plant construction project always involves lots of activities. Precise information about the activities duration is unfortunately unavailable due to the uncertain resources capacity. The fuzzy program evaluation and review technique (PERT has been widely applied to solve the fuzzy project scheduling problem. This paper presents an extended fuzzy PERT approach with four major improvement aspects to support the construction project scheduling management: 1 Evaluate operation fuzzy times based on available working volumes, resources quantity and fuzzy capacity of resources, 2 Adopting a maximal alpha_i-level cut method to compare the fuzzy precedent activities times to determine the reasonable earliest starting times of each activity, 3 Using fuzzy algebra method instead of fuzzy subtraction method to compute the fuzzy latest starting times and 4 Developing a project scheduling risk index (PSRI to assist the decision maker to evaluate the project scheduling risk. Simulations experiments are conducted and demonstrated satisfactory results.

  9. Fuzzy-rough set and fuzzy ID3 decision approaches to knowledge discovery in datasets

    Directory of Open Access Journals (Sweden)

    O. G. Elbarbary

    2012-07-01

    Full Text Available Fuzzy rough sets are the generalization of traditional rough sets to deal with both fuzziness and vagueness in data. The existing researches on fuzzy rough sets mainly concentrate on the construction of approximation operators. Less effort has been put on the knowledge discovery in datasets with fuzzy rough sets. This paper mainly focuses on knowledge discovery in datasets with fuzzy rough sets. After analyzing the previous works on knowledge discovery with fuzzy rough sets, we introduce formal concepts of attribute reduction with fuzzy rough sets and completely study the structure of attribute reduction.

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

    OpenAIRE

    Goutam Kumar Bose; Nikhil Chandra Chatterjee

    2016-01-01

    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...

  11. Object–Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set

    Directory of Open Access Journals (Sweden)

    Liu Yaya

    2017-03-01

    Full Text Available The research on incomplete fuzzy soft sets is an integral part of the research on fuzzy soft sets and has been initiated recently. In this work, we first point out that an existing approach to predicting unknown data in an incomplete fuzzy soft set suffers from some limitations and then we propose an improved method. The hidden information between both objects and parameters revealed in our approach is more comprehensive. Furthermore, based on the similarity measures of fuzzy sets, a new adjustable object-parameter approach is proposed to predict unknown data in incomplete fuzzy soft sets. Data predicting converts an incomplete fuzzy soft set into a complete one, which makes the fuzzy soft set applicable not only to decision making but also to other areas. The compared results elaborated through rate exchange data sets illustrate that both our improved approach and the new adjustable object-parameter one outperform the existing method with respect to forecasting accuracy.

  12. Fuzzy Inspired Hybrid Genetic Approach to Optimize Travelling Salesman Problem

    Directory of Open Access Journals (Sweden)

    Bindu

    2012-06-01

    Full Text Available One of the category of algorithm Problems are basically exponential problems. These problems are basically exponential problems and take time to find the solution. In the present work we are optimising one of the common NP complete problem called Travelling Salesman Problem. In our work we have defined a genetic approach by combining fuzzy approach along with genetics. In this work we have implemented the modified DPX crossover to improve genetic approach. The work is implemented in MATLAB environment and obtained results shows the define approach has optimized the existing genetic algorithm results

  13. FORECASTING INFLATION RATES WITH HIGH ORDER FUZZY TIME SERIES APPROACH

    Directory of Open Access Journals (Sweden)

    VEDİDE REZAN USLU

    2013-06-01

    Full Text Available To obtain inflation forecasts is an important economic issue. The more accurate forecasts we get implies the more precise decisions we make. The central Bank reports inflation rates in certain periods of every year. In this reports the results of inflation expectation survey are presented. In this study we use an approach in which relationship is determined by artificial neural network in high order fuzzy time series model. Time series of consumer price index is estimated by both the artificial neural network based method and some fuzzy approaches which is common in the literature. The results are compared to the results of inflation expectation survey analysis conducted by Central Bank of the Republic of Turkey in the aspect of forecasts accuracy.

  14. Rule based fuzzy logic approach for classification of fibromyalgia syndrome.

    Science.gov (United States)

    Arslan, Evren; Yildiz, Sedat; Albayrak, Yalcin; Koklukaya, Etem

    2016-06-01

    Fibromyalgia syndrome (FMS) is a chronic muscle and skeletal system disease observed generally in women, manifesting itself with a widespread pain and impairing the individual's quality of life. FMS diagnosis is made based on the American College of Rheumatology (ACR) criteria. However, recently the employability and sufficiency of ACR criteria are under debate. In this context, several evaluation methods, including clinical evaluation methods were proposed by researchers. Accordingly, ACR had to update their criteria announced back in 1990, 2010 and 2011. Proposed rule based fuzzy logic method aims to evaluate FMS at a different angle as well. This method contains a rule base derived from the 1990 ACR criteria and the individual experiences of specialists. The study was conducted using the data collected from 60 inpatient and 30 healthy volunteers. Several tests and physical examination were administered to the participants. The fuzzy logic rule base was structured using the parameters of tender point count, chronic widespread pain period, pain severity, fatigue severity and sleep disturbance level, which were deemed important in FMS diagnosis. It has been observed that generally fuzzy predictor was 95.56 % consistent with at least of the specialists, who are not a creator of the fuzzy rule base. Thus, in diagnosis classification where the severity of FMS was classified as well, consistent findings were obtained from the comparison of interpretations and experiences of specialists and the fuzzy logic approach. The study proposes a rule base, which could eliminate the shortcomings of 1990 ACR criteria during the FMS evaluation process. Furthermore, the proposed method presents a classification on the severity of the disease, which was not available with the ACR criteria. The study was not limited to only disease classification but at the same time the probability of occurrence and severity was classified. In addition, those who were not suffering from FMS were

  15. Subway Train Braking System: A Fuzzy Based Hardware Approach

    Directory of Open Access Journals (Sweden)

    Mamun B.I. Reaz

    2011-01-01

    Full Text Available Problem statement: Automated subway train-braking system require perfection, efficiency and fast response. In order to cope with this concerns, an appropriate algorithm need to be developed which need to be implemented in hardware for faster response. Approach: In this research, the FPGA realization of fuzzy based subway train braking system has been presented on an Alter FLEX10K device to provide an accurate and increased speed of convergence of the network. The fuzzy based subway train braking system is comprised of fusilier, inference, rule selector and defuzzifier modules. Sixteen rules are identified for the rule selector module. After determining the membership functions and its fuzzy variables, the Max-Min Composition method and Madman-Min implication operator are used for the inference module and the Centre of Gravity method is used for the defuzzification module. Each module is modeled individually using behavioral VHDL. The layers are then connected using structural VHDL. Two 8-bit and one 8-bit unsigned digital signals are used for input and output respectively. Six ROMs are defined in order to decrease the chances of processing and increasing the throughput of the system. Results: Functional simulations were commenced to verify the functionality of the individual modules and the system as well. We have validated the hardware implementation of the proposed approach through comparison, verification and analysis. The design has utilized 2372 units of LC with a system frequency of 139.8MHz. Conclusion: In this research, the FPGA realization of fuzzy brake system of subway train has been successfully implemented with minimum usage of logic cells. The validation study with C model shows that the hardware model is appropriate and the hardware approach shows faster and accurate response with full automatic control.

  16. 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 ...

  17. A New Fuzzy Approach for Dynamic Load Balancing Algorithm

    CERN Document Server

    Karimi, Abbas; Jantan, Adznan b; Ramli, A R; Saripan, M Iqbal b

    2009-01-01

    Load balancing is the process of improving the Performance of a parallel and distributed system through is distribution of load among the processors [1-2]. Most of the previous work in load balancing and distributed decision making in general, do not effectively take into account the uncertainty and inconsistency in state information but in fuzzy logic, we have advantage of using crisps inputs. In this paper, we present a new approach for implementing dynamic load balancing algorithm with fuzzy logic, which can face to uncertainty and inconsistency of previous algorithms, further more our algorithm shows better response time than round robin and randomize algorithm respectively 30.84 percent and 45.45 percent.

  18. A New Fuzzy Approach for Dynamic Load Balancing Algorithm

    Directory of Open Access Journals (Sweden)

    Abbas Karimi

    2009-10-01

    Full Text Available Load balancing is the process of improving the Performance of a parallel and distributed system through is distribution of load among the processors [1-2]. Most of the previous work in load balancing and distributed decision making in general, do not effectively take into account the uncertainty and inconsistency in state information but in fuzzy logic, we have advantage of using crisps inputs. In this paper,we present a new approach for implementing dynamic load balancing algorithm with fuzzy logic, which can face to uncertainty and inconsistency of previous algorithms, further more our algorithm shows better response time than round robin and randomize algorithm respectively 30.84% and 45.45%.

  19. Adaptive Neuro-fuzzy approach in friction identification

    Science.gov (United States)

    Zaiyad Muda @ Ismail, Muhammad

    2016-05-01

    Friction is known to affect the performance of motion control system, especially in terms of its accuracy. Therefore, a number of techniques or methods have been explored and implemented to alleviate the effects of friction. In this project, the Artificial Intelligent (AI) approach is used to model the friction which will be then used to compensate the friction. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is chosen among several other AI methods because of its reliability and capabilities of solving complex computation. ANFIS is a hybrid AI-paradigm that combines the best features of neural network and fuzzy logic. This AI method (ANFIS) is effective for nonlinear system identification and compensation and thus, being used in this project.

  20. MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH

    Directory of Open Access Journals (Sweden)

    Özlem TÜRKŞEN

    2012-06-01

    Full Text Available The most widely used approach for solving multi response surface problems is response surface methodology. It is thought to be that the response surface methodology is inadequate for evaluation ofunexplained vagueness in real world problems. Therefore in the study, fuzzy approach is proposed as an alternative to solve the multi response surface problems. The main aim of this study is to representthe applicability of the fuzzy approach for solving of the multi-response problems in which the probability distributions of the response variables cannot be determined. At the modeling stage, the fuzzy least squares regression analysis, based on Diamond's distance metric, is used. In the optimization stage, the problem is considered as a fuzzy multi-objective optimization problem. NondominatedSorting Genetic Algorithm-II (NSGA-II, defined in the literature, is adapted by using centroid index fuzzy ranking approach then called Fuzzy NSGA-II (FNSGA-II. Fuzzy Pareto solution set is obtainedby optimizing the problem, which is composed of fuzzy objective functions, with FNSGA-II. The proposed fuzzy solution approaches are applied on a data set defined in the literature. Thus, it is seen thatan obtained fuzzy Pareto solution is a set of acceptable different response values for the performed multi-response experiments at the defined levels of input variables.

  1. A cloud-based fuzzy approach for spatial site selection in decision support system

    Institute of Scientific and Technical Information of China (English)

    FU Xiao-xi; Byeong-Seob You; XIA Ying; Gyung-Bae Kim; Hae-Young Bae

    2007-01-01

    In decision support system for spatial site selection, the fuzzy synthetic evaluation is a useful way. However, the method can't pay attention to the randomness in factors. To remedy the problem, this paper proposes a clouded-base fuzzy approach which combines advantages of cloud transform and fuzzy synthetic evaluation. The cloud transform considers the randomness in the factors and product the higher concept layer for data mining. At the same time, the check mechanism controls the quality of partitions in factors. Then the fuzzy approach was used to get final evaluation value with randomness and fuzziness. It make the final result is optimization. Finally, performance evaluations show that this approach spent less runtime and got more accuracy than the fuzzy synthetic. The experiments prove that the proposed method is faster and more accuracy than the original method.

  2. A neuro approach to solve fuzzy Riccati differential equations

    Science.gov (United States)

    Shahrir, Mohammad Shazri; Kumaresan, N.; Kamali, M. Z. M.; Ratnavelu, Kurunathan

    2015-10-01

    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.

  3. 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.

  4. Bi-Objective Bilevel Programming Problem: A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Haseen S.

    2015-12-01

    Full Text Available In this paper, a likely situation of a set of decision maker’s with bi-objectives in case of fuzzy multi-choice goal programming is considered. The problem is then carefully formulated as a bi-objective bilevel programming problem (BOBPP with multiple fuzzy aspiration goals, fuzzy cost coefficients and fuzzy decision variables. Using Ranking method the fuzzy bi-objective bilevel programming problem (FBOBPP is converted into a crisp model. The transformed problem is further solved by adopting a two level Stackelberg game theory and fuzzy decision model of Sakawa. A numerical with hypothetical values is also used to illustrate the problem.

  5. Comprehensive evaluation of water resources security in the Yellow River basin based on a Fuzzy Multi-Attribute Decision Analysis Approach

    Directory of Open Access Journals (Sweden)

    K. K. Liu

    2014-01-01

    Full Text Available In this paper, a Fuzzy Multi-Attribute Decision Analysis Approach (FMADAA was adopted in water resources security evaluation for the nine provinces in the Yellow River basin in 2006. A numerical approximation system and a modified left-right scoring approach were adopted to cope with the uncertainties in the acquired information. Four multi-attribute decision making methods were implemented in the evaluation model for impact evaluation, including simple weighted addition (SWA, weighted product (WP, cooperative game theory (CGT and technique for order preference by similarity to ideal solution (TOPSIS which could be used for helping rank the water resources security in those nine provinces as well as the criteria alternatives. Moreover, several aggregation methods including average ranking procedure, borda and copeland methods were used to integrate the ranking results. The ranking results showed that the water resources security of the entire basin is in critical, insecurity and absolute insecurity state, especially in Shanxi, Inner Mongolia and Ningxia provinces in which water resources were lower than the average quantity in China. Hence, future planning of the Yellow River basin should mainly focus on the improvement of water eco-environment status in the provinces above.

  6. Comprehensive evaluation of water resources security in the Yellow River basin based on a fuzzy multi-attribute decision analysis approach

    Science.gov (United States)

    Liu, K. K.; Li, C. H.; Cai, Y. P.; Xu, M.; Xia, X. H.

    2014-05-01

    In this paper, a fuzzy multi-attribute decision analysis approach (FMADAA) was developed for supporting the evaluation of water resources security in nine provinces within the Yellow River basin. A numerical approximation system and a modified left-right scoring approach were adopted to cope with the uncertainties in the acquired information. Also, four conventional multi-attribute decision analysis (MADA) methods were implemented in the evaluation model for impact evaluation, including simple weighted addition (SWA), weighted product (WP), cooperative game theory (CGT) and technique for order preference by similarity to ideal solution (TOPSIS). Moreover, several aggregation methods including average ranking procedure, Borda and Copeland methods were used to integrate the ranking results, helping rank the water resources security in those nine provinces as well as improving reliability of evaluation results. The ranking results showed that the water resources security of the entire basin was in critical condition, including the insecurity and absolute insecurity states, especially in Shanxi, Inner Mongolia and Ningxia provinces in which water resources were lower than the average quantity in China. Hence, the improvement of water eco-environment statuses in the above-mentioned provinces should be prioritized in the future planning of the Yellow River basin.

  7. Fuzzy Temporal Clustering Approach for E-Commerce Websites

    Directory of Open Access Journals (Sweden)

    Sudhamathy G.

    2012-07-01

    Full Text Available In this paper a novel approach for clustering of web logs data and to predict intelligent recommendations on the E-Commerce web sites is proposed so as to improve the marketing strategy and to improve customer loyalty. Fuzzy Temporal Clustering Approach (FTCA performs clustering of the web site visitors and the web site pages based on the frequency of visit and time spent. Time plays a crucial role in the analysis of web usage. Hence these clusters are studied over a period of time to study the migration behaviour of the users and the pages across periods. Such a study can provide intelligentrecommendations for the E-Commerce web sites that focus on specific product recommendations and behavioural targeting. Experimental evaluation of the method has proved that this approach FTCA is most efficient, easy to use and a useful clustering approach.

  8. A Novel Approach for Shearer Memory Cutting Based on Fuzzy Optimization Method

    Directory of Open Access Journals (Sweden)

    Xin Zhou

    2013-01-01

    Full Text Available In order to improve the implement precision of shearer memory cutting, a novel approach based on the coal floor height variation which is taken as a significant factor and fuzzy optimization theory is proposed. The problem of shearer memory cutting is analyzed and the mathematic model is established. Moreover, the key technologies such as fuzzy control model, quantitative factors, and fuzzy control rules are elaborated, and the flowchart of shearer memory cutting method based on fuzzy optimization theory is designed. Finally, a simulation example is carried out and the proposed approach is proved feasible and efficient.

  9. Fuzzy Logic Approaches to Multi-Objective Decision-Making in Aerospace Applications

    Science.gov (United States)

    Hardy, Terry L.

    1994-01-01

    Fuzzy logic allows for the quantitative representation of multi-objective decision-making problems which have vague or fuzzy objectives and parameters. As such, fuzzy logic approaches are well-suited to situations where alternatives must be assessed by using criteria that are subjective and of unequal importance. This paper presents an overview of fuzzy logic and provides sample applications from the aerospace industry. Applications include an evaluation of vendor proposals, an analysis of future space vehicle options, and the selection of a future space propulsion system. On the basis of the results provided in this study, fuzzy logic provides a unique perspective on the decision-making process, allowing the evaluator to assess the degree to which each option meets the evaluation criteria. Future decision-making should take full advantage of fuzzy logic methods to complement existing approaches in the selection of alternatives.

  10. 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.

  11. A New Approach of Fuzzy Theory with Uncertainties in Geographic Information Systems

    OpenAIRE

    Mohammad Bazmara; Fereshteh Mohammadi

    2013-01-01

    Until now, fuzzy logic has been extensively used to better analyze and design controllers for chemical processes. It has also been used for other applications like parameter estimation of nonlinear continuous-time systems but in general fuzzy logic has been intensively used for heuristics based system. Recently, fuzzy logic has been applied successfully in many areas where conventional model based approaches are difficult or not cost effective to implement. Mechanistic modeling of physical sy...

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

    OpenAIRE

    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...

  13. A Neuro-Fuzzy Approach in the Prediction of Financial Stability and Distress Periods

    OpenAIRE

    Giovanis, eleftheios

    2008-01-01

    The purpose of this paper is to present a neuro-fuzzy approach of financial distress pre-warning model appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) from 2002 through 2008. We present an adaptive neuro-fuzzy system with triangle and Gaussian membership functions. We conclude that neuro-fuzzy model presents almost perfect forecasts for financial distress periods as also...

  14. 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.

  15. 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.

  16. A Simple Fuzzy Logic Approach for Induction Motors Stator Condition Monitoring

    Directory of Open Access Journals (Sweden)

    M. Zeraoulia

    2005-03-01

    Full Text Available Many researches dealt with the problem of induction motors fault detection and diagnosis. The major difficulty is the lack of an accurate model that describes a fault motor. Moreover, experienced engineers are often required to interpret measurement data that are frequently inconclusive. A fuzzy logic approach may help to diagnose induction motor faults. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. Therefore, this paper applies fuzzy logic to induction motors fault detection and diagnosis. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. The induction motor condition is diagnosed using a compositional rule of fuzzy inference.

  17. A Novel Approach to Modeling of Hydrogeologic Systems Using Fuzzy Differential Equations

    Science.gov (United States)

    Faybishenko, B. A.

    2003-12-01

    The many simultaneously occurring processes in unsaturated-saturated heterogeneous soils and fractured rocks can cause field observations to become imprecise and incomplete. Consequently, the results of predictions using deterministic and stochastic mathematical models are often uncertain, vague or "fuzzy." One of the alternative approaches to modeling hydrogeologic systems is the application of a fuzzy-systems approach, which is already widely used in such fields as engineering, physics, chemistry, and biology. After presenting a hydrogeologic system as a fuzzy system, the author presents a fuzzy form of Darcy's equation. Based on this equation, second-order fuzzy partial differential equations of the elliptic type (analogous to the Laplace equation) and the parabolic type (analogous to the Richards equation) are derived. These equations are then approximated as fuzzy-difference equations and solved using the basic principles of fuzzy arithmetic. The solutions for the fuzzy-difference equations take the form of fuzzy membership functions for each observation point (node). The author gives examples of the solutions of these equations for flow in unsaturated and saturated media and then compares them with those obtained using deterministic and stochastic methods.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Fuzzy-Rule-Based Approach for Modeling Sensory Acceptabitity of Food Products

    Directory of Open Access Journals (Sweden)

    Olusegun Folorunso

    2009-04-01

    Full Text Available The prediction of product acceptability is often an additive effect of individual fuzzy impressions developed by a consumer on certain underlying attributes characteristic of the product. In this paper, we present the development of a data-driven fuzzy-rule-based approach for predicting the overall sensory acceptability of food products, in this case composite cassava-wheat bread. The model was formulated using the Takagi-Sugeno and Kang (TSK fuzzy modeling approach. Experiments with the model derived from sampled data were simulated on Windows 2000XP running on Intel 2Gh environment. The fuzzy membership function for the sensory scores is implemented in MATLAB 6.0 using the fuzzy logic toolkit, and weights of each linguistic attribute were obtained using a Correlation Coefficient formula. The results obtained are compared to those of human judgments. Overall assessments suggest that, if implemented, this approach will facilitate a better acceptability of cassava bread as well as nutritionally improved food.

  3. Fuzzy-logic approach to HTR nuclear power plant model control

    Energy Technology Data Exchange (ETDEWEB)

    Bubak, M.; Moscinski, J. (Akademia Gorniczo-Hutnicza, Krakow (Poland)); Jewulski, J. (Institute of Physical Chemistry, Krakow (Poland))

    1983-01-01

    The fuzzy-set theory is used to incorporate linguistic 'rules of the thumb' of a human operator in the HTR nuclear power plant controller. The results of the extensive computer simulations are encouraging and confirm the usefulness of this approach in nuclear power plant control. In the Appendix, a short introduction to fuzzy logic is given.

  4. Knowledge Acquisition in MedFrame/Cadiag: A Generalized Fuzzy Approach

    OpenAIRE

    1996-01-01

    We propose a stepwise knowledge acquisition approach based on fuzzy set theory to support the development and refinement of medical knowledge bases. The definition of fuzzy relationships between medical entities allows to represent knowledge at different levels of precision. The definition of relationships is supported by the use of linguistic variables and a semi-automatic knowledge acquisition program.

  5. A Framework to Measure the Service Quality of Distributor with Fuzzy Graph Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Tarun Kumar Gupta

    2016-01-01

    Full Text Available A combination of fuzzy logic and graph theoretic approach has been used to find the service quality of distributor in a manufacturing supply chain management. This combination is termed as the fuzzy graph theoretic (FGT approach. Initially the identified factors were grouped by SPSS (statistical package for social science software and then the digraph approach was applied. The interaction and inheritance values were calculated by fuzzy graph theory approach in terms of permanent function. Then a single numerical index was calculated by using permanent function which indicates the distributor service quality. This method can be used to compare the service quality of different distributors.

  6. A Novel Multiple Attribute Satisfaction Evaluation Approach with Hesitant Intuitionistic Linguistic Fuzzy Information

    Directory of Open Access Journals (Sweden)

    Shanghong Yang

    2014-01-01

    Full Text Available This paper investigates the multiple attribute decision making (MADM problems in which the attribute values take the form of hesitant intuitionistic linguistic fuzzy element (HILFE. Firstly, motivated by the idea of intuitionistic linguistic variables (ILVs and hesitant fuzzy elements (HFEs, the concept, operational laws, and comparison laws of HILFE are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic linguistic fuzzy information, such as hesitant intuitionistic linguistic fuzzy weighted aggregation operators, hesitant intuitionistic linguistic fuzzy ordered weighted aggregation operators, and generalized hesitant intuitionistic linguistic fuzzy weighted aggregation operators. Moreover, some desirable properties of these operators and the relationships between them are discussed. Based on the hesitant intuitionistic linguistic fuzzy weighted average (HILFWA operator and the hesitant intuitionistic linguistic fuzzy weighted geometric (HILFWG operator, an approach for evaluating satisfaction degree is proposed under hesitant intuitionistic linguistic fuzzy environment. Finally, a practical example of satisfaction evaluation for milk products is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness.

  7. 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.

  8. An Efficient Fuzzy Clustering-Based Approach for Intrusion Detection

    CERN Document Server

    Nguyen, Huu Hoa; Darmont, Jérôme

    2011-01-01

    The need to increase accuracy in detecting sophisticated cyber attacks poses a great challenge not only to the research community but also to corporations. So far, many approaches have been proposed to cope with this threat. Among them, data mining has brought on remarkable contributions to the intrusion detection problem. However, the generalization ability of data mining-based methods remains limited, and hence detecting sophisticated attacks remains a tough task. In this thread, we present a novel method based on both clustering and classification for developing an efficient intrusion detection system (IDS). The key idea is to take useful information exploited from fuzzy clustering into account for the process of building an IDS. To this aim, we first present cornerstones to construct additional cluster features for a training set. Then, we come up with an algorithm to generate an IDS based on such cluster features and the original input features. Finally, we experimentally prove that our method outperform...

  9. Probabilistic Fuzzy Goal Programming Problems Involving Pareto Distribution: Some Additive Approaches

    Directory of Open Access Journals (Sweden)

    S.K. Barik

    2015-06-01

    Full Text Available In many real-life decision making problems, probabilistic fuzzy goal programming problems are used where some of the input parameters of the problem are considered as random variables with fuzzy aspiration levels. In the present paper, a linearly constrained probabilistic fuzzy goal programming programming problem is presented where the right hand side parameters in some constraints follows Pareto distribution with known mean and variance. Also the aspiration levels are considered as fuzzy. Further, simple, weighted, and preemptive additive approaches are discussed for probabilistic fuzzy goal programming model. These additive approaches are employed to aggregating the membership values and form crisp equivalent deterministic models. The resulting models are then solved by using standard linear mathematical programming techniques. The developed methodology and solution procedures are illustrated with a numerical example.

  10. Rough Set Approach to Approximation Reduction in Ordered Decision Table with Fuzzy Decision

    Directory of Open Access Journals (Sweden)

    Xiaoyan Zhang

    2011-01-01

    Full Text Available In practice, some of information systems are based on dominance relations, and values of decision attribute are fuzzy. So, it is meaningful to study attribute reductions in ordered decision tables with fuzzy decision. In this paper, upper and lower approximation reductions are proposed in this kind of complicated decision table, respectively. Some important properties are discussed. The judgement theorems and discernibility matrices associated with two reductions are obtained from which the theory of attribute reductions is provided in ordered decision tables with fuzzy decision. Moreover, rough set approach to upper and lower approximation reductions is presented in ordered decision tables with fuzzy decision as well. An example illustrates the validity of the approach, and results show that it is an efficient tool for knowledge discovery in ordered decision tables with fuzzy decision.

  11. A novel computational approach to approximate fuzzy interpolation polynomials.

    Science.gov (United States)

    Jafarian, Ahmad; Jafari, Raheleh; Mohamed Al Qurashi, Maysaa; Baleanu, Dumitru

    2016-01-01

    This paper build a structure of fuzzy neural network, which is well sufficient to gain a fuzzy interpolation polynomial of the form [Formula: see text] where [Formula: see text] is crisp number (for [Formula: see text], which interpolates the fuzzy data [Formula: see text]. Thus, a gradient descent algorithm is constructed to train the neural network in such a way that the unknown coefficients of fuzzy polynomial are estimated by the neural network. The numeral experimentations portray that the present interpolation methodology is reliable and efficient.

  12. Effect of fuzzy partitioning in Crohn's disease classification: a neuro-fuzzy-based approach.

    Science.gov (United States)

    Ahmed, Sk Saddam; Dey, Nilanjan; Ashour, Amira S; Sifaki-Pistolla, Dimitra; Bălas-Timar, Dana; Balas, Valentina E; Tavares, João Manuel R S

    2017-01-01

    Crohn's disease (CD) diagnosis is a tremendously serious health problem due to its ultimately effect on the gastrointestinal tract that leads to the need of complex medical assistance. In this study, the backpropagation neural network fuzzy classifier and a neuro-fuzzy model are combined for diagnosing the CD. Factor analysis is used for data dimension reduction. The effect on the system performance has been investigated when using fuzzy partitioning and dimension reduction. Additionally, further comparison is done between the different levels of the fuzzy partition to reach the optimal performance accuracy level. The performance evaluation of the proposed system is estimated using the classification accuracy and other metrics. The experimental results revealed that the classification with level-8 partitioning provides a classification accuracy of 97.67 %, with a sensitivity and specificity of 96.07 and 100 %, respectively.

  13. Fuzzy Neighborhood Allocation (FNA): A Fuzzy Approach to Improve Near Neighborhood Allocation in DDB

    Science.gov (United States)

    Basseda, Reza; Rahgozar, Maseud; Lucas, Caro

    Allocating data fragments in distributed database systems is an important issue in distributed database (DDB) systems. In this paper, we are going to improve the effectiveness of current NNA algorithm using a Fuzzy inference engine. Results indicate that, our fuzzy based NNA algorithm leads 5% gain in some of systems performance metrics. This algorithm, providing a data clustering mechanism, which is very suitable for DDBS in the networks, with heavy traffic loads, and frequent data access requests.

  14. Intrusion detection: a novel approach that combines boosting genetic fuzzy classifier and data mining techniques

    Science.gov (United States)

    Ozyer, Tansel; Alhajj, Reda; Barker, Ken

    2005-03-01

    This paper proposes an intelligent intrusion detection system (IDS) which is an integrated approach that employs fuzziness and two of the well-known data mining techniques: namely classification and association rule mining. By using these two techniques, we adopted the idea of using an iterative rule learning that extracts out rules from the data set. Our final intention is to predict different behaviors in networked computers. To achieve this, we propose to use a fuzzy rule based genetic classifier. Our approach has two main stages. First, fuzzy association rule mining is applied and a large number of candidate rules are generated for each class. Then the rules pass through pre-screening mechanism in order to reduce the fuzzy rule search space. Candidate rules obtained after pre-screening are used in genetic fuzzy classifier to generate rules for the specified classes. Classes are defined as Normal, PRB-probe, DOS-denial of service, U2R-user to root and R2L- remote to local. Second, an iterative rule learning mechanism is employed for each class to find its fuzzy rules required to classify data each time a fuzzy rule is extracted and included in the system. A Boosting mechanism evaluates the weight of each data item in order to help the rule extraction mechanism focus more on data having relatively higher weight. Finally, extracted fuzzy rules having the corresponding weight values are aggregated on class basis to find the vote of each class label for each data item.

  15. 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...

  16. A New Approach for Solving Fully Fuzzy Linear Systems

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2011-01-01

    Full Text Available Several authors have proposed different methods to find the solution of fully fuzzy linear systems (FFLSs that is, fuzzy linear system with fuzzy coefficients involving fuzzy variables. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are nonnegative fuzzy numbers. In this paper a new method is proposed to solve an FFLS with arbitrary coefficients and arbitrary solution vector, that is, there is no restriction on the elements that have been used in the FFLS. The primary objective of this paper is thus to introduce the concept and a computational method for solving FFLS with no non negative constraint on the parameters. The method incorporates the principles of linear programming in solving an FFLS with arbitrary coefficients and is not only easier to understand but also widens the scope of fuzzy linear equations in scientific applications. To show the advantages of the proposed method over existing methods we solve three FFLSs.

  17. 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.

  18. Risk analysis with a fuzzy-logic approach of a complex installation

    Science.gov (United States)

    Peikert, Tim; Garbe, Heyno; Potthast, Stefan

    2016-09-01

    This paper introduces a procedural method based on fuzzy logic to analyze systematic the risk of an electronic system in an intentional electromagnetic environment (IEME). The method analyzes the susceptibility of a complex electronic installation with respect to intentional electromagnetic interference (IEMI). It combines the advantages of well-known techniques as fault tree analysis (FTA), electromagnetic topology (EMT) and Bayesian networks (BN) and extends the techniques with an approach to handle uncertainty. This approach uses fuzzy sets, membership functions and fuzzy logic to handle the uncertainty with probability functions and linguistic terms. The linguistic terms add to the risk analysis the knowledge from experts of the investigated system or environment.

  19. AN APPROACH TO GROUP DECISION MAKING BASED ON INTERVAL FUZZY PREFERENCE RELATIONS

    Institute of Scientific and Technical Information of China (English)

    Yunliang JIANG

    2007-01-01

    In this paper,we investigate group decision making problems where the decision information given by decision makers takes the form of interval fuzzy preference relations.We first give an index to measure the similarity degree of two interval fuzzy preference relations,and utilize the similarity index to check the consistency degree of group opinion.Furthermore,we use the error-propagation principle to determine the priority vector of the aggregated matrix,and then develop an approach to group decision making based on interval fuzzy preference relations.Finally,we give an example to illustrate the developed approach.

  20. A Fuzzy Simulation-Based Optimization Approach for Groundwater Remediation Design at Contaminated Aquifers

    Directory of Open Access Journals (Sweden)

    A. L. Yang

    2012-01-01

    Full Text Available A fuzzy simulation-based optimization approach (FSOA is developed for identifying optimal design of a benzene-contaminated groundwater remediation system under uncertainty. FSOA integrates remediation processes (i.e., biodegradation and pump-and-treat, fuzzy simulation, and fuzzy-mean-value-based optimization technique into a general management framework. This approach offers the advantages of (1 considering an integrated remediation alternative, (2 handling simulation and optimization problems under uncertainty, and (3 providing a direct linkage between remediation strategies and remediation performance through proxy models. The results demonstrate that optimal remediation alternatives can be obtained to mitigate benzene concentration to satisfy environmental standards with a minimum system cost.

  1. A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

    Science.gov (United States)

    Shehadeh, Hana; Lea, Robert N.

    1992-01-01

    Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

  2. Costal vulnerability systems-network using Fuzzy and Bayesian approaches

    Science.gov (United States)

    Taramelli, A.; Valentini, E.; Filipponi, F.; Nguyen Xuan, A.; Arosio, M.

    2016-12-01

    Marine drivers such as surge in the context of SLR, are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assesment, management and planning (e.g. the role of dune ridges in surge mitigation and climate adaptation) can enhance the resilience of coastal systems. In this frame assessing the vulnerability is a key concern of many 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, etc.. To this end it is unclear how SLR, subsidence and erosion might affect coastal subsistence resources because of highly complex interactions and because of the subjective system of weighting many variables and their interaction within the systems. In this contribution, making the best use of many EO products, in situ data and modelling, we propose a multidimensional surge vulnerability assessment that aims at combining together geophysical and socioeconomic variable on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian approach. The final goal is providing insight in understanding how to quantify regulating ecosystem services.

  3. 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.

  4. 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.

  5. Inexact fuzzy integer chance constraint programming approach for noise control within an urban environment

    Science.gov (United States)

    Huang, Kai; Huang, Gordon; Dai, Liming; Fan, Yurui

    2016-08-01

    This article introduces an inexact fuzzy integer chance constraint programming (IFICCP) approach for identifying noise reduction strategy under uncertainty. The IFICCP method integrates the interval programming and fuzzy chance constraint programming approaches into a framework, which is able to deal with uncertainties expressed as intervals and fuzziness. The proposed IFICCP model can be converted into two deterministic submodels corresponding to the optimistic and pessimistic conditions. The modelling approach is applied to a hypothetical control measure selection problem for noise reduction. Results of the case study indicate that useful solutions for noise control practices can be acquired. Three acceptable noise levels for two communities are considered. For each acceptable noise level, several decision alternatives have been obtained and analysed under different fuzzy confidence levels, which reflect the trade-offs between environmental and economic considerations.

  6. A New Approach of Fuzzy Theory with Uncertainties in Geographic Information Systems

    Directory of Open Access Journals (Sweden)

    Mohammad Bazmara

    2013-01-01

    Full Text Available Until now, fuzzy logic has been extensively used to better analyze and design controllers for chemical processes. It has also been used for other applications like parameter estimation of nonlinear continuous-time systems but in general fuzzy logic has been intensively used for heuristics based system. Recently, fuzzy logic has been applied successfully in many areas where conventional model based approaches are difficult or not cost effective to implement. Mechanistic modeling of physical systems is often complicated by the presence of uncertainties. When models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outcomes. A systematic uncertainty analysis provides insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. In this paper, generalized fuzzy α-cut is used to show the utility of fuzzy approach in uncertainty analysis of pollutant transport in ground water. Based on the concept of transformation method which is an extension of α-cuts, the approach shows superiority over conventional methods of uncertainty modeling. A 2-D groundwater transport model has been used to show the utility of this approach. Results are compared with commonly used probabilistic method and normal Fuzzy alpha-cut technique. In order to provide a basis for comparison between the two approaches, the shape of the membership functions used in the fuzzy methods are the same as the shape of the probability density function used in the Monte-Carlo method. The extended fuzzy α-cut technique presents a strong alternative to the conventional approach.

  7. 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.

  8. Fuzzy set theoretic approach to fault tree analysis

    African Journals Online (AJOL)

    user

    Research in conventional fault tree analysis (FTA) is based mainly on failure ... Thus for a very complex system having large number of components, the ..... Smaller, the triangular fuzzy number B-Ai, will result in the best approximation for B.

  9. A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection

    Directory of Open Access Journals (Sweden)

    Dalton Meitei Thounaojam

    2016-01-01

    Full Text Available This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy system. Experimental results show that the accuracy of the shot boundary detection increases with the increase in iterations or generations of the GA optimization process. The proposed system is compared to latest techniques and yields better result in terms of F1score parameter.

  10. A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection.

    Science.gov (United States)

    Thounaojam, Dalton Meitei; Khelchandra, Thongam; Manglem Singh, Kh; Roy, Sudipta

    2016-01-01

    This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy system. Experimental results show that the accuracy of the shot boundary detection increases with the increase in iterations or generations of the GA optimization process. The proposed system is compared to latest techniques and yields better result in terms of F1score parameter.

  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. MODELLING OF AIR CONDITIONING SYSTEM BY FUZZY LOGIC APPROACH

    Directory of Open Access Journals (Sweden)

    Ahmet ÖZEK

    2004-03-01

    Full Text Available One of the main problems in control systems is the difficulty to form the mathematical model associated with the control mechanism. Even though this model can be formed, to realize the application with conventional logic may cause very complex problems. The fuzzy logic without using mathematical model of control system can create control mechanism only with the help of linguistic variables. In this article the modeling has been realized by fuzzy logic.

  13. 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.

  14. A fuzzy approach to the Weighted Overlap Dominance model

    DEFF Research Database (Denmark)

    Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt

    2013-01-01

    Decision support models are required to handle the various aspects of multi-criteria decision problems in order to help the individual understand its possible solutions. In this sense, such models have to be capable of aggregating and exploiting different types of measurements and evaluations in ...... is presented for ordering and identifying the best alternatives under an interactive procedure that takes into account the natural imprecision and relevance of information....... in an interactive way, where input data can take the form of uniquely-graded or interval-valued information. Here we explore the Weighted Overlap Dominance (WOD) model from a fuzzy perspective and its outranking approach to decision support and multidimensional interval analysis. Firstly, imprecision measures...... are introduced for characterizing the type of uncertainty being expressed by intervals, examining at the same time how the WOD model handles both non-interval as well as interval data, and secondly, relevance degrees are proposed for obtaining a ranking over the alternatives. Hence, a complete methodology...

  15. A Novel Multicriteria Group Decision Making Approach With Intuitionistic Fuzzy SIR Method

    CERN Document Server

    Chai, Junyi

    2011-01-01

    The superiority and inferiority ranking (SIR) method is a generation of the well-known PROMETHEE method, which can be more efficient to deal with multi-criterion decision making (MCDM) problem. Intuitionistic fuzzy sets (IFSs), as an important extension of fuzzy sets (IFs), include both membership functions and non-membership functions and can be used to, more precisely describe uncertain information. In real world, decision situations are usually under uncertain environment and involve multiple individuals who have their own points of view on handing of decision problems. In order to solve uncertainty group MCDM problem, we propose a novel intuitionistic fuzzy SIR method in this paper. This approach uses intuitionistic fuzzy aggregation operators and SIR ranking methods to handle uncertain information; integrate individual opinions into group opinions; make decisions on multiple-criterion; and finally structure a specific decision map. The proposed approach is illustrated in a simulation of group decision ma...

  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

    Science.gov (United States)

    Khalfi, B.; de Runz, C.; Faiz, S.; Akdag, H.

    2015-08-01

    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. Extraction of rules for faulty bearing classification by a Neuro-Fuzzy approach

    Science.gov (United States)

    Marichal, G. N.; Artés, Mariano; García Prada, J. C.; Casanova, O.

    2011-08-01

    In this paper, a classification system of faulty bearings based on a Neuro-Fuzzy approach is presented. The vibration signals in the frequency domain produced by the faulty bearings will be taken as the inputs to the classification system. In this sense, it is an essential characteristic for the used Neuro-Fuzzy approach, the possibility of taking a great number of inputs. The system consists of several Neuro-Fuzzy systems for determining different bearing status, along with a measurement equipment of the vibration spectral data. In this paper, a special attention is focused on the analysis of the rules obtained by the final Neuro-Fuzzy system. In fact, a rule extraction process and an interpretation rule process is discussed. Several trials have been carried out, taking into account the vibration spectral data collected by the measurement equipment, where satisfactory results have been achieved.

  19. 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...... applications. To this end, a methodology based on model simulations is used that employs three statistical methods: (i) Monte-Carlo procedure: to find proper initial conditions, (ii) Identifiability analysis: to find an identifiable parameter subset of the fuzzy controller and (iii) minimization algorithm......: to fine-tune the identifiable parameter subset of the controller. Indeed, the initial location found by Monte-Carlo simulations provided better results than using trial and error approach when identifying parameters of the fuzzy controller. The identifiable subset was reduced to 4 parameters from a total...

  20. 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.

  1. A Neuro-Fuzzy Approach for Modelling Electricity Demand in Victoria

    OpenAIRE

    Abraham, Ajith; Nath, Baikunth

    2004-01-01

    Neuro-fuzzy systems have attracted growing interest of researchers in various scientific and engineering areas due to the increasing need of intelligent systems. This paper evaluates the use of two popular soft computing techniques and conventional statistical approach based on Box--Jenkins autoregressive integrated moving average (ARIMA) model to predict electricity demand in the State of Victoria, Australia. The soft computing methods considered are an evolving fuzzy neural network (EFuNN) ...

  2. An Approach for Solving Goal Programming Problems using Interval Type-2 Fuzzy Goals

    Directory of Open Access Journals (Sweden)

    Juan Carlos Figueroa-García

    2015-08-01

    Full Text Available This paper presents a proposal for solving goal problems involving multiple experts opinions and perceptions. In goal programming problems where no statistical data about their goals exist, the use of information coming from experts becomes the last reliable source. This way, we propose an approach to model this kind of goals using Interval Type-2 fuzzy sets, and a simple method for finding an optimal solution based on previous methods that have been proposed for classical fuzzy sets.

  3. Design Method for the Magnetic Bearing Control System with Fuzzy-PID Approach

    Institute of Scientific and Technical Information of China (English)

    XU Chun-guang; L(U) Dong-ming; HAO Juan

    2008-01-01

    The five degree freedom magnetic bearing is researched and its structure and working principles are introduced also.Based on the fuzzy control technology,combining fuzzy algorithm and PID control method,identifying the transition process mode of the online system to get the PID parameters'self-adjusting,the magnetic bearing system's Fuzzy-PID nonlinear controller is designed by analyzing the system control demands.The Fuzzy-PID nonlinear controller can deal with the magnetic bearing system's open loop instability and strong nonlinearity,and the approach could improve the system's rapidity,adaptability,stability and dynamic characteristics.Comparative analysis and experiments are conducted between linear PID and nonlinear fuzzyPID control methods,the results show that the fuzzy-PID controller is better,and the five-freedom magnetic bearing's rotary precision experiments are conducted by the fuzzy-PID controller,it satisfies the control rotary precision demands and realizes the bearing's steady floating and rotating.

  4. 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...

  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 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.

  7. An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination.

    Science.gov (United States)

    Li, Jianbing; Huang, Gordon H; Zeng, Guangming; Maqsood, Imran; Huang, Yuefei

    2007-01-01

    An integrated fuzzy-stochastic risk assessment (IFSRA) approach was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with site conditions, environmental guidelines, and health impact criteria. The contaminant concentrations in groundwater predicted from a numerical model were associated with probabilistic uncertainties due to the randomness in modeling input parameters, while the consequences of contaminant concentrations violating relevant environmental quality guidelines and health evaluation criteria were linked with fuzzy uncertainties. The contaminant of interest in this study was xylene. The environmental quality guideline was divided into three different strictness categories: "loose", "medium" and "strict". The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base. The ER and HR risk levels were divided into five categories of "low", "low-to-medium", "medium", "medium-to-high" and "high", respectively. The general risk levels included six categories ranging from "low" to "very high". The fuzzy membership functions of the related fuzzy events and the fuzzy rule base were established based on a questionnaire survey. Thus the IFSRA integrated fuzzy logic, expert involvement, and stochastic simulation within a general framework. The robustness of the modeling processes was enhanced through the effective reflection of the two types of uncertainties as compared with the conventional risk assessment approaches. The developed IFSRA was applied to a petroleum-contaminated groundwater system in western Canada. Three scenarios with different environmental quality guidelines were analyzed, and reasonable results were obtained. The risk assessment approach developed in this study offers a unique tool for systematically quantifying various uncertainties in contaminated site management, and it also

  8. 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.

  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. A neuro-fuzzy approach in the classification of students' academic performance.

    Science.gov (United States)

    Do, Quang Hung; Chen, Jeng-Fung

    2013-01-01

    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.

  11. A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting

    Directory of Open Access Journals (Sweden)

    Leandro Maciel

    2012-09-01

    Full Text Available Forecasting stock market returns volatility is a challenging task that has attracted the attention of market practitioners, regulators and academics in recent years. This paper proposes a Fuzzy GJR-GARCH model to forecast the volatility of S&P 500 and Ibovespa indexes. The model comprises both the concept of fuzzy inference systems and GJR-GARCH modeling approach in order to consider the principles of time-varying volatility, leverage effects and volatility clustering, in which changes are cataloged by similarity. Moreover, a differential evolution (DE algorithm is suggested to solve the problem of Fuzzy GJR-GARCH parameters estimation. The results indicate that the proposed method offers significant improvements in volatility forecasting performance in comparison with GARCH-type models and with a current Fuzzy-GARCH model reported in the literature. Furthermore, the DE-based algorithm aims to achieve an optimal solution with a rapid convergence rate.

  12. Possibility Distribution-Based Approach for MAGDM With Hesitant Fuzzy Linguistic Information.

    Science.gov (United States)

    Wu, Zhibin; Xu, Jiuping

    2016-03-01

    In group decision making (GDM) with qualitative settings, experts may require several possible linguistic values rather than a single term to express their preferences. A hesitant fuzzy linguistic term set has recently been developed to manage this situation. In line with this development, in this paper, we present a new framework model to address multiple attribute GDM with hesitant fuzzy linguistic information. First, the concept of a possibility distribution is defined. Based on the possibility distributions, some aggregation operators such as the hesitant fuzzy linguistic weighted average operator and the hesitant fuzzy linguistic ordered weighted average operator are proposed. A consensus measure is then defined and a consensus reaching process is given which uses different identification and direction rules compared with the existing methods. A selection process is also described to rank the alternatives. Both processes are necessary to support stakeholders when making rational decisions. Finally, two simulated examples are given to verify the practicability of the proposed approach.

  13. A gradient-descent-based approach for transparent linguistic interface generation in fuzzy models.

    Science.gov (United States)

    Chen, Long; Chen, C L Philip; Pedrycz, Witold

    2010-10-01

    Linguistic interface is a group of linguistic terms or fuzzy descriptions that describe variables in a system utilizing corresponding membership functions. Its transparency completely or partly decides the interpretability of fuzzy models. This paper proposes a GRadiEnt-descEnt-based Transparent lInguistic iNterface Generation (GREETING) approach to overcome the disadvantage of traditional linguistic interface generation methods where the consideration of the interpretability aspects of linguistic interface is limited. In GREETING, the widely used interpretability criteria of linguistic interface are considered and optimized. The numeric experiments on the data sets from University of California, Irvine (UCI) machine learning databases demonstrate the feasibility and superiority of the proposed GREETING method. The GREETING method is also applied to fuzzy decision tree generation. It is shown that GREETING generates better transparent fuzzy decision trees in terms of better classification rates and comparable tree sizes.

  14. 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

  15. 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.

  16. Fault Detection in Systems-A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Ashok Kumar

    2004-04-01

    Full Text Available The task of fault detection is important when dealing with failures of crucial nature. After detection of faults in a system, it is advisable to suggest maintenance action before occurrenceof a failure. Fault detection may be done by observing various symptoms of the system during its operational stage. Sometimes, symptoms cannot be quantified easily but can be expressedin linguistic terms. Since linguistic terms are fuzzy quantifiers, these can be represented by fuzzy numbers. In this paper, two cases have been discussed, where a fault likely to affect a particular systemlsystems, is detected. In the first case, this is done by means of a compositional rule of inference. The second case is based on modified similarity measure. For both these  cases, linguistic terms have been expressed as trapezoidal fuzzy numbers

  17. Fuzzy unit commitment solution - A novel twofold simulated annealing approach

    Energy Technology Data Exchange (ETDEWEB)

    Saber, Ahmed Yousuf; Senjyu, Tomonobu; Yona, Atsushi; Urasaki, Naomitsu [Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho Nakagami, Okinawa 903-0213 (Japan); Funabashi, Toshihisa [Meidensha Corporation, Riverside Building 36-2, Tokyo 103-8515 (Japan)

    2007-10-15

    The authors propose a twofold simulated annealing (twofold-SA) method for the optimization of fuzzy unit commitment formulation in this paper. In the proposed method, simulated annealing (SA) and fuzzy logic are combined to obtain SA acceptance probabilities from fuzzy membership degrees. Fuzzy load is calculated from error statistics and an initial solution is generated by a priority list method. The initial solution is decomposed into hourly-schedules and each hourly-schedule is modified by decomposed-SA using a bit flipping operator. Fuzzy membership degrees are the selection attributes of the decomposed-SA. A new solution consists of these hourly-schedules of entire scheduling period after repair, as unit-wise constraints may not be fulfilled at the time of an individual hourly-schedule modification. This helps to detect and modify promising schedules of appropriate hours. In coupling-SA, this new solution is accepted for the next iteration if its cost is less than that of current solution. However, a higher cost new solution is accepted with the temperature dependent total cost membership function. Computation time of the proposed method is also improved by the imprecise tolerance of the fuzzy model. Besides, excess units with the system dependent probability distribution help to handle constraints efficiently and imprecise economic load dispatch (ELD) calculations are modified to save the execution time. The proposed method is tested using standard reported data sets. Numerical results show an improvement in solution cost and time compared to the results obtained from other existing methods. (author)

  18. 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.

  19. Neural fuzzy inference network approach to maneuvering target tracking

    Institute of Scientific and Technical Information of China (English)

    韩红; 刘允才; 韩崇昭; 朱洪艳; 文戎

    2004-01-01

    In target tracking study, the fast target maneuver detecting and highly accurate tracking are very important.And it is difficult to be solved. For the radar/infrared image fused tracking system, a extend Kalman filter combines with a neural fuzzy inference network to be used in maneuvering target tracking. The features related to the target maneuver are extracted from radar, infrared measurements and outputs of tracking filter, and are sent into the neural fuzzy inference network as inputs firstly, and then the target's maneuver inputs are estimated, so that, the accurate tracking is achieved. The simulation results indicate that the new method is valuable for maneuvering target tracking.

  20. Decision Support for Participatory Forest Planning Using AHP and TOPSIS

    Directory of Open Access Journals (Sweden)

    Hilma Nilsson

    2016-05-01

    Full Text Available Long-term forest management planning often involves several stakeholders with conflicting objectives, creating a complex decision process. Multiple-criteria decision analysis (MCDA presents a promising framework for finding solutions in terms of suitable trade-offs among the objectives. However, many of the MCDA methods that have been implemented in forest management planning can only be used to compare and evaluate a limited number of management plans, which increases the risk that the most suitable plan is not included in the decision process. The aim of this study is to test whether the combination of two MCDA methods can facilitate the evaluation of a large number of strategic forest management plans in a situation with multiple objectives and several stakeholders. The Analytic Hierarchy Process (AHP was used to set weights for objectives based on stakeholder preferences and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS was used to produce an overall ranking of alternatives. This approach was applied to a case study of the Vilhelmina municipality, northern Sweden. The results show that the combination of AHP and TOPSIS is easy to implement in participatory forest planning and takes advantage of the capacity of forest decision support systems to create a wide array of management plans. This increases the possibility that the most suitable plan for all stakeholders will be identified.

  1. 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.

  2. 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.

  3. 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.

  4. Fuzzy indicator approach: development of impact factor of soil amendments

    Science.gov (United States)

    Soil amendments have been shown to be useful for improving soil condition, but it is often difficult to make management decisions as to their usefulness. Utilization of Fuzzy Set Theory is a promising method for decision support associated with utilization of soil amendments. In this article a tool ...

  5. Professional Learning: A Fuzzy Logic-Based Modelling Approach

    Science.gov (United States)

    Gravani, M. N.; Hadjileontiadou, S. J.; Nikolaidou, G. N.; Hadjileontiadis, L. J.

    2007-01-01

    Studies have suggested that professional learning is influenced by two key parameters, i.e., climate and planning, and their associated variables (mutual respect, collaboration, mutual trust, supportiveness, openness). In this paper, we applied analysis of the relationships between the proposed quantitative, fuzzy logic-based model and a series of…

  6. A Fuzzy Set Theory Approach to Periodical Binding Decisions.

    Science.gov (United States)

    Turner, Stephen J.; O'Brien, Gregory

    1984-01-01

    Results of data analysis on 470 journal titles illustrate complexity of the fuzzy set theory modeling process, which consists of three factors--number of missing issues, citations, circulations--and its limitations in making journal binding decisions. Procedures of research, data collection, and data analysis are discussed. Matrices are included.…

  7. 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.

  8. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    P Senthilkumar; G Rajendran

    2011-12-01

    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.

  9. Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

    Institute of Scientific and Technical Information of China (English)

    Xin Li; Xue-Ping Zhao; Jie Chen

    2009-01-01

    Pressure ripples in electric power steering (EPS) systems can be caused by the phase lag between the driver's steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno (T-S) fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation (PDC) structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality (LMI) problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

  10. A State Recognition Approach for Complex Equipment Based on a Fuzzy Probabilistic Neural Network

    Directory of Open Access Journals (Sweden)

    Jing Xu

    2016-05-01

    Full Text Available Due to the traditional state recognition approaches for complex electromechanical equipment having had the disadvantages of excessive reliance on complete expert knowledge and insufficient training sets, real-time state identification system was always difficult to be established. The running efficiency cannot be guaranteed and the fault rate cannot be reduced fundamentally especially in some extreme working conditions. To solve these problems, an online state recognition method for complex equipment based on a fuzzy probabilistic neural network (FPNN was proposed in this paper. The fuzzy rule base for complex equipment was established and a multi-level state space model was constructed. Moreover, a probabilistic neural network (PNN was applied in state recognition, and the fuzzy functions and quantification matrix were presented. The flowchart of proposed approach was designed. Finally, a simulation example of shearer state recognition and the industrial application with an accuracy of 90.91% were provided and the proposed approach was feasible and efficient.

  11. A fuzzy Bayesian approach to flood frequency estimation with imprecise historical information

    Science.gov (United States)

    Salinas, José Luis; Kiss, Andrea; Viglione, Alberto; Viertl, Reinhard; Blöschl, Günter

    2016-09-01

    This paper presents a novel framework that links imprecision (through a fuzzy approach) and stochastic uncertainty (through a Bayesian approach) in estimating flood probabilities from historical flood information and systematic flood discharge data. The method exploits the linguistic characteristics of historical source material to construct membership functions, which may be wider or narrower, depending on the vagueness of the statements. The membership functions are either included in the prior distribution or the likelihood function to obtain a fuzzy version of the flood frequency curve. The viability of the approach is demonstrated by three case studies that differ in terms of their hydromorphological conditions (from an Alpine river with bedrock profile to a flat lowland river with extensive flood plains) and historical source material (including narratives, town and county meeting protocols, flood marks and damage accounts). The case studies are presented in order of increasing fuzziness (the Rhine at Basel, Switzerland; the Werra at Meiningen, Germany; and the Tisza at Szeged, Hungary). Incorporating imprecise historical information is found to reduce the range between the 5% and 95% Bayesian credibility bounds of the 100 year floods by 45% and 61% for the Rhine and Werra case studies, respectively. The strengths and limitations of the framework are discussed relative to alternative (non-fuzzy) methods. The fuzzy Bayesian inference framework provides a flexible methodology that fits the imprecise nature of linguistic information on historical floods as available in historical written documentation.

  12. 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.

  13. New approach to solve fully fuzzy system of linear equations using single and double parametric form of fuzzy numbers

    Indian Academy of Sciences (India)

    Diptiranjan Behera; S Chakraverty

    2015-02-01

    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 for the first time in this paper for the present analysis. Using single parametric form, the $n \\times n$ fully fuzzy system of linear equations have been converted to a $2n \\times 2n$ crisp system of linear equations. On the other hand, double parametric form of fuzzy numbers converts the n×n fully fuzzy system of linear equations to a crisp system of same order. Triangular and trapezoidal convex normalized fuzzy sets are used for the present analysis. Known example problems are solved to illustrate the efficacy and reliability of the proposed methods.

  14. A New Approach for Lossless Image Compression Based on Fuzzy Adaptive Prediction

    Institute of Scientific and Technical Information of China (English)

    Wu Yingqian(吴颖谦); Fang Tao; Shi Pengfei

    2004-01-01

    This paper proposes a novel approach for image lossless compression based on fuzzy logic and adaptive prediction. By a flexible strategy, the method can acquire a set of original predictors describing the more detail characteristic. Using a neural network, the proposed method can more efficiently organize the training of original predictors and implement adaptive prediction in fuzzy style. In entropy coding phase, the context-based conditional adaptive arithmetic encoding is adopted. The experiments demonstrate the characteristics make the approach achieve good tradeoff between computational complexity and efficiency of prediction and good performance for lossless compression.

  15. 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

  16. Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approaches

    Directory of Open Access Journals (Sweden)

    Patel M.G.C.

    2015-03-01

    Full Text Available The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations. The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource consuming.

  17. 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.

  18. Fuzzy Decision-Making Approach in Geometric Programming for a Single Item EOQ Model

    Directory of Open Access Journals (Sweden)

    Monalisha Pattnaik

    2015-06-01

    Full Text Available Background and methods: Fuzzy decision-making approach is allowed in geometric programming for a single item EOQ model with dynamic ordering cost and demand-dependent unit cost. The setup cost varies with the quantity produced/purchased and the modification of objective function with storage area in the presence of imprecisely estimated parameters are investigated.  It incorporates all concepts of a fuzzy arithmetic approach, the quantity ordered, and demand per unit compares both fuzzy geometric programming technique and other models for linear membership functions.  Results and conclusions: Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated through an example problem and the results discu ssed. Sensitivity analysis of the optimal solution is also studied with respect to changes in different parameter values.  

  19. A New Approach of Learning Hierarchy Construction Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Ali AAJLI

    2014-10-01

    Full Text Available In recent years, adaptive learning systems rely increasingly on learning hierarchy to customize the educational logic developed in their courses. Most approaches do not consider that the relationships of prerequisites between the skills are fuzzy relationships. In this article, we describe a new approach of a practical application of fuzzy logic techniques to the construction of learning hierarchies. For this, we use a learning hierarchy predefined by one or more experts of a specific field. However, the relationships of prerequisites between the skills in the learning hierarchy are not definitive and they are fuzzy relationships. Indeed, we measure relevance degree of all relationships existing in this learning hierarchy and we try to answer to the following question: Is the relationships of prerequisites predefined in initial learning hierarchy are correctly established or not?

  20. A New Approach to Lung Image Segmentation using Fuzzy Possibilistic C-Means Algorithm

    CERN Document Server

    Gomathi, M

    2010-01-01

    Image segmentation is a vital part of image processing. Segmentation has its application widespread in the field of medical images in order to diagnose curious diseases. The same medical images can be segmented manually. But the accuracy of image segmentation using the segmentation algorithms is more when compared with the manual segmentation. In the field of medical diagnosis an extensive diversity of imaging techniques is presently available, such as radiography, computed tomography (CT) and magnetic resonance imaging (MRI). Medical image segmentation is an essential step for most consequent image analysis tasks. Although the original FCM algorithm yields good results for segmenting noise free images, it fails to segment images corrupted by noise, outliers and other imaging artifact. This paper presents an image segmentation approach using Modified Fuzzy C-Means (FCM) algorithm and Fuzzy Possibilistic c-means algorithm (FPCM). This approach is a generalized version of standard Fuzzy CMeans Clustering (FCM) ...

  1. Multilevel Fuzzy Approach to the Risk and Disaster Management

    Directory of Open Access Journals (Sweden)

    Márta Takács

    2010-11-01

    Full Text Available In this paper a short general review of the main characteristics of riskmanagement applications is given, where a hierarchical, multilevel risk managementmethod can be applied in a fuzzy decision making environment. The given case study is atravel risk-level calculation based on the presented model. In the last section an extendedmodel and a preliminary mathematical description is presented, where the pairwisecomparison matrix of the grouped risk factors expands the previous principles.

  2. The multidimensional measurement of poverty: a fuzzy set approach

    Directory of Open Access Journals (Sweden)

    Michele Costa

    2013-05-01

    Full Text Available By using fuzzy set theory a multidimensional analysis of poverty of Italian households is performed on the basis of SHIW data. A set of composite indicators is constructed in order to analyze different dimensions of poverty. For each indicator is calculated an unidimensional poverty ratio, thus allowing a comparison among indicators on the dimensions of poverty. Finally, a multidimensional poverty ratio is obtained.

  3. 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,

  4. Image Retrieval Approach Based on Intuitive Fuzzy Set Combined with Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-yin; XU Wei-hua; HU Chang-zhen

    2009-01-01

    Aiming at shortcomings of traditional image retrieval systems,a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed.Each image is segmented into a constant number of sub-images in vertical direction.Color features are extracted from every sub-image to get chromosome coding.It is considered that fuzzy membership and intuitive fuzzy hesitancy degree of every pixel's color in image are associated to all the color histogram bins.Certain feature,fuzzy feature and intuitive fuzzy feature of colors in an image,are used together to describe the content of image.Efficient combinations of sub-image are selected according to operation of selecting,crossing and variation.Retrieval resuits are obtained from image matching based on these color feature combinations of sub-images.Tests show that this approach can improve the accuracy of image retrieval in the case of not decreasing the speed of image retrieval.Its mean precision is above 80%.

  5. 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.

  6. 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.

  7. TOPSIS Evaluation Method on "Have Both Hard and Soft" Systems

    Institute of Scientific and Technical Information of China (English)

    CHEN Shi-lian

    2001-01-01

    In "Have Both Hard and Soft" systems, the soft targets and hard targets are divided into twodistinct target system. The measured results of soft target system are regarded as a matrix with intervalnumbers. On the basis of Topsis method, we discuss a new Topsis evaluation method on "Have Both Hardand Soft" systems, which combined soft targets with hard targets.

  8. Assessment of safety and health in the tea industry of Barak valley, Assam: a fuzzy logic approach.

    Science.gov (United States)

    Gupta, Rajat; Dey, Sanjoy Kumar

    2013-01-01

    Traditional safety and health system measurement procedures, practiced in various industries produce qualitative results with a degree of uncertainty. This paper presents a fuzzy-logic-based approach to developing a fuzzy model for assessing the safety and health status in the tea industry. For this, the overall safety and health status at a tea estate has been considered as a function of 4 inputs: occupational safety, occupational health, behavioral safety and competency. A set of fuzzy rules based on expert human judgment has been used to correlate different fuzzy inputs and output. Fuzzy set operations are used to calculate the safety and health status of the tea industry. Application of the developed model at a tea estate showed that the safety and health status belongs to the fuzzy class of good with a crisp value of 7.2.

  9. A fuzzy-based approach for open-transistor fault diagnosis in voltage-source inverter induction motor drives

    Science.gov (United States)

    Zhang, Jianghan; Luo, Hui; Zhao, Jin; Wu, Feng

    2015-02-01

    This paper develops a novel method for the detection and isolation of open-transistor faults in voltage-source inverters feeding induction motors. Based on analyzing the load currents trajectories after Concordia transformation, six diagnostic signals each of which indicates a certain switch are extracted and a fuzzy rule base is designed to perform fuzzy reasoning in order to detect and isolate 21 fault modes including single- and double-transistor faults. In addition, the fuzzy rules are rearranged and each of them is set to a reasonable value representing the fault modes. The simulation and experiment are carried out to demonstrate the effectiveness of the proposed fuzzy approach.

  10. A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

    Science.gov (United States)

    Vadiati, M; Asghari-Moghaddam, A; Nakhaei, M; Adamowski, J; Akbarzadeh, A H

    2016-12-15

    Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI). In an effort to present generalized hybrid fuzzy indices a significant effort was made to employ well-known groundwater quality index acceptability ranges as fuzzy model output ranges rather than employing expert knowledge in the fuzzification of output parameters. The proposed approach was evaluated for its ability to assess the drinking water quality of 49 samples collected seasonally from groundwater resources in Iran's Sarab Plain during 2013-2014. Input membership functions were defined as "desirable", "acceptable" and "unacceptable" based on expert knowledge and the standard and permissible limits prescribed by the World Health Organization. Output data were categorized into multiple categories based on the GQI (5 categories), WQI (5 categories), and GWQI (3 categories). Given the potential of fuzzy models to minimize uncertainties, hybrid fuzzy-based indices produce significantly more accurate assessments of groundwater quality than traditional indices. The developed models' accuracy was assessed and a comparison of the performance indices demonstrated the Fuzzy Groundwater Quality Index model to be more accurate than both the Fuzzy Water Quality Index and Fuzzy Ground Water Quality Index models. This suggests that the new hybrid fuzzy

  11. 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.

  12. Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Presents the mobile robots dynamic motion planning problem with a task to find an obstacle-free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti mal rule base given and the simulation results showing its effectiveness.

  13. H(infinity) output tracking control for nonlinear systems via T-S fuzzy model approach.

    Science.gov (United States)

    Lin, Chong; Wang, Qing-Guo; Lee, Tong Heng

    2006-04-01

    This paper studies the problem of H(infinity) output tracking control for nonlinear time-delay systems using Takagi-Sugeno (T-S) fuzzy model approach. An LMI-based design method is proposed for achieving the output tracking purpose. Illustrative examples are given to show the effectiveness of the present results.

  14. A Fuzzy Genetic Algorithm Approach to an Adaptive Information Retrieval Agent.

    Science.gov (United States)

    Martin-Bautista, Maria J.; Vila, Maria-Amparo; Larsen, Henrik Legind

    1999-01-01

    Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)

  15. Robust controller design for fuzzy parametric uncertain systems: an optimal control approach.

    Science.gov (United States)

    Patre, Balasaheb M; Bhiwani, R J

    2013-03-01

    A new approach of designing a robust controller for fuzzy parametric uncertain systems is proposed. A linear time invariant (LTI) system with fuzzy coefficients is called as fuzzy parametric uncertain system (FPUS). The proposed method envisages conversion of the FPUS into an uncertain (interval) state space controllable canonical form system in terms of its alpha cut. Further, the problem of designing a robust controller is translated into an optimal control problem minimizing a cost function. For matched uncertainty, it is shown that the optimal control problem is a linear quadratic regulator (LQR) problem, which can be solved to obtain a robust controller for FPUS. The numerical examples and simulation results show the effectiveness of the proposed method in terms of robustness of the controller. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

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

    Institute of Scientific and Technical Information of China (English)

    P. Balasubramaniam; M. Kalpana; R. Rakkiyappan

    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.

  17. A Fuzzy Approach of the Optimal Analysis Based of Failure States in Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    E. Minca

    2012-12-01

    Full Text Available This article proposes an algorithm for prognosis in optimal analysis of manufacturing systems. Uncertain knowledge of such task requires for specific reasoning and adaptive model base of fuzzy logic analyzes. The proposed method performs the interfaces between the results provided by the fuzzy supervision model and the algorithm witch identify the real state of the monitored system. The supervisory system sends failure signals described in a fuzzy approach. These ones represent inputs values in the system of failure optimal analysis which identifies the current degradation states by recurrent identification cycle. The proposed algorithm has also predictive component capable to determine the possible evolution of the system state towards a critical state of failure.

  18. Weighted Additive Fuzzy Goal Programming Approach to Aggregate Production Planning

    Directory of Open Access Journals (Sweden)

    Mohammed. Mekidiche

    2013-03-01

    Full Text Available This study presents a new formulation of Weighted Additive fuzzy goal programming model developed by Yaghoobi and Tamiz [21]. and Yaghoobi et al [22] for aggregate production planning (WAFGP-APP, The proposed formulation attempts to minimize total production and work force costs, carrying inventory costs and rates of changes in Work force. A real-world industrial case study demonstrates applicability of proposed model to practical APP decision problems. LINGO computer package has been used to solve final crisp linear programming problem package and getting optimal production plan.

  19. 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.

  20. Answer Set Programming for Continuous Domains A Fuzzy Logic Approach

    CERN Document Server

    Janssen, Jeroen; Vermeir, Dirk

    2012-01-01

    "Answer set programming (ASP)" is a declarative language tailored towards solving combinatorial optimization problems. It has been successfully applied to e.g. planning problems, configuration and verification of software, diagnosis and database repairs. However, ASP is not directly suitable for modeling problems with continuous domains. Such problems occur naturally in diverse fields such as the design of gas and electricity networks, computer vision and investment portfolios. To overcome this problem we study FASP, a combination of ASP with fuzzy logic - a class of manyvalued logic

  1. 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.

  2. An improved a-cut approach to transforming fuzzy membership function into basic belief assignment

    Institute of Scientific and Technical Information of China (English)

    Yang Yi; X.Rong Li; Han Deqiang

    2016-01-01

    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 uncer-tainty representation into the basic belief assignment are needed. a-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 a-cut approach caused by its normalization step are pointed out in this paper. An improved a-cut approach is pro-posed, which can counteract the drawbacks of the traditional a-cut approach and has good prop-erties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved a-cut approach.

  3. 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.

  4. Composite Fuzzy Logic Control Approach to a Flexible Joint Manipulator

    Directory of Open Access Journals (Sweden)

    Mohd Ashraf Ahmad

    2013-01-01

    Full Text Available The raised complicatedness of the dynamics of a robot manipulator considering joint elasticity makes conventional model‐based control strategies complex and hard to synthesize. This paper presents investigations into the development of hybrid intelligent control schemes for the trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, a collocated proportional‐derivative (PD‐type Fuzzy Logic Controller (FLC is first developed for the tip angular position control of a flexible joint manipulator. This is then extended to incorporate a non‐collocated Fuzzy Logic Controller, a non‐collocated proportional‐ integral‐derivative (PID and an input‐shaping scheme for the vibration reduction of the flexible joint system. The positive zero‐vibration‐derivative‐derivative (ZVDD shaper is designed based on the properties of the system. The implementation results of the response of the flexible joint manipulator with the controllers are presented in time and frequency domains. The performances of the hybrid control schemes are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed.

  5. A fuzzy approach to selecting roof supports in longwall mining

    Directory of Open Access Journals (Sweden)

    Yetkin, M. E.

    2016-05-01

    Full Text Available As a decision-making problem, selecting proper machines and equipment plays a key role for mining sites and companies. Many factors affect this decision, and values belonging to these factors can be expressed numerically and/or non-numerically. In order to make the most appropriate decision, engineers must carry out an evaluation process that comprises all criteria that might affect decision-making. To achieve this, multi-criteria decision-making tools are used. As a result of technological developments, coal outputs in longwall mining have risen tremendously over the last decades, and longwall mechanisation has become unavoidable. The significance of powered roof supports in particular increases day- by-day, since the rate of roof support has to be in accordance with the rate of face advance in longwalls. In this study, an integrated fuzzy analytic hierarchy process and fuzzy goal programming model is used to select the most suitable powered roof supports. The procedure is applied to a real-life underground coal mine that is operated using the longwall method. Seven alternative powered roof supports are compared with each other, taking a total of 24 decision criteria under four main topics into account. In conclusion, the most suitable roof supports for the mine under study are determined and recommended to the decision-makers of the system.

  6. Adaptively managing wildlife for climate change: a fuzzy logic approach.

    Science.gov (United States)

    Prato, Tony

    2011-07-01

    Wildlife managers have little or no control over climate change. However, they may be able to alleviate potential adverse impacts of future climate change by adaptively managing wildlife for climate change. In particular, wildlife managers can evaluate the efficacy of compensatory management actions (CMAs) in alleviating potential adverse impacts of future climate change on wildlife species using probability-based or fuzzy decision rules. Application of probability-based decision rules requires managers to specify certain probabilities, which is not possible when they are uncertain about the relationships between observed and true ecological conditions for a species. Under such uncertainty, the efficacy of CMAs can be evaluated and the best CMA selected using fuzzy decision rules. The latter are described and demonstrated using three constructed cases that assume: (1) a single ecological indicator (e.g., population size for a species) in a single time period; (2) multiple ecological indicators for a species in a single time period; and (3) multiple ecological conditions for a species in multiple time periods.

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

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    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.

  8. Some properties of fuzzy soft proximity spaces.

    Science.gov (United States)

    Demir, İzzettin; Özbakır, Oya Bedre

    2015-01-01

    We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities.

  9. Some Properties of Fuzzy Soft Proximity Spaces

    Science.gov (United States)

    Demir, İzzettin; Özbakır, Oya Bedre

    2015-01-01

    We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities. PMID:25793224

  10. 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.

  11. Capacity planning for waste management systems: an interval fuzzy robust dynamic programming approach.

    Science.gov (United States)

    Nie, Xianghui; Huang, Guo H; Li, Yongping

    2009-11-01

    This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information.

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

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    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.

  13. Predicting Suicide Attacks: A Fuzzy Soft Set Approach

    CERN Document Server

    Kharal, Athar

    2010-01-01

    This paper models a decision support system to predict the occurance of suicide attack in a given collection of cities. The system comprises two parts. First part analyzes and identifies the factors which affect the prediction. Admitting incomplete information and use of linguistic terms by experts, as two characteristic features of this peculiar prediction problem we exploit the Theory of Fuzzy Soft Sets. Hence the Part 2 of the model is an algorithm vz. FSP which takes the assessment of factors given in Part 1 as its input and produces a possibility profile of cities likely to receive the accident. The algorithm is of O(2^n) complexity. It has been illustrated by an example solved in detail. Simulation results for the algorithm have been presented which give insight into the strengths and weaknesses of FSP. Three different decision making measures have been simulated and compared in our discussion.

  14. Social scientists in public health: a fuzzy approach.

    Science.gov (United States)

    do Nascimento, Juliana Luporini; Stephan, Celso; Nunes, Everardo Duarte

    2015-05-01

    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.

  15. 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.

  16. 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.

  17. 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.

  18. A Fuzzy Co-Clustering approach for Clickstream Data Pattern

    CERN Document Server

    Rathipriya, R

    2011-01-01

    Web Usage mining is a very important tool to extract the hidden business intelligence data from large databases. The extracted information provides the organizations with the ability to produce results more effectively to improve their businesses and increasing of sales. Co-clustering is a powerful bipartition technique which identifies group of users associated to group of web pages. These associations are quantified to reveal the users' interest in the different web pages' clusters. In this paper, Fuzzy Co-Clustering algorithm is proposed for clickstream data to identify the subset of users of similar navigational behavior /interest over a subset of web pages of a website. Targeting the users group for various promotional activities is an important aspect of marketing practices. Experiments are conducted on real dataset to prove the efficiency of proposed algorithm. The results and findings of this algorithm could be used to enhance the marketing strategy for directing marketing, advertisements for web base...

  19. A Multiple Model Approach to Modeling Based on Fuzzy Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    冯瑞; 张艳珠; 宋春林; 邵惠鹤

    2003-01-01

    A new multiple models(MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines (F SVMs). By applying the proposed approach to a pH neutralization titration experi-ment, F_SVMs MM not only provides satisfactory approximation and generalization property, but also achieves superior performance to USOCPN multiple modeling method and single modeling method based on standard SVMs.

  20. Usability Evaluation of Software Systems using Fuzzy Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    Anubha Gulati

    2012-05-01

    Full Text Available Over the past few decades, Usability has emerged as an extremely important quality factor. Many methods have so far been proposed for usability evaluation but they lack in one way or another. This paper proposes a method for software usability quantification using the fuzzy multiple criteria weighted average approach. This approach has been chosen due to the highly unpredictable nature of the attributes on which usability depends. A case study is presented to prove the feasibility of the quantification technique.

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

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    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.

  2. 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.

  3. 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.

  4. Station-keeping control for a stratospheric airship platform via fuzzy adaptive backstepping approach

    Science.gov (United States)

    Yang, Yueneng; Wu, Jie; Zheng, Wei

    2013-04-01

    This paper presents a novel approach for station-keeping control of a stratospheric airship platform in the presence of parametric uncertainty and external disturbance. First, conceptual design of the stratospheric airship platform is introduced, including the target mission, configuration, energy sources, propeller and payload. Second, the dynamics model of the airship platform is presented, and the mathematical model of its horizontal motion is derived. Third, a fuzzy adaptive backstepping control approach is proposed to develop the station-keeping control system for the simplified horizontal motion. The backstepping controller is designed assuming that the airship model is accurately known, and a fuzzy adaptive algorithm is used to approximate the uncertainty of the airship model. The stability of the closed-loop control system is proven via the Lyapunov theorem. Finally, simulation results illustrate the effectiveness and robustness of the proposed control approach.

  5. 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.

  6. QUADRATIC BI-LEVEL PROGRAMMING PROBLEM BASED ON FUZZY GOAL PROGRAMMING APPROACH

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    Partha Pratim Dey

    2011-11-01

    Full Text Available This paper presents fuzzy goal programming approach to quadratic bi-level programming problem. Inthe model formulation of the problem, we construct the quadratic membership functions by determiningindividual best solutions of the quadratic objective functions subject to the system constraints. Thequadratic membership functions are then transformed into equivalent linear membership functions byfirst order Taylor series approximation at the individual best solution point. Since the objectives of upperand lower level decision makers are potentially conflicting in nature, a possible relaxation of each leveldecisions are considered by providing preference bounds on the decision variables for avoiding decisiondeadlock. Then fuzzy goal programming approach is used for achieving highest degree of each of themembership goals by minimizing deviational variables. Numerical examples are provided in order todemonstrate the efficiency of the proposed approach.

  7. 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)

  8. Bi-Level Multi-Objective Absolute-Value Fractional programming Problems: A Fuzzy Goal Programming approach

    Directory of Open Access Journals (Sweden)

    Mansour Saraj

    2012-06-01

    Full Text Available In this paper we propose a fuzzy goal programming method for obtaining a satisfactory solution to a bi-level multi-objective absolute-value fractional programming (BLMO-A-FP problems. In the proposed approach, the membership functions for the de ned fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by upper level decision maker (ULDM are developed in the model formulation of the problem. Then fuzzy goal programming technique is used for achieving highest degree of each of the membership goals by minimizing negative and positive deviational variables. The method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem eciently by using linear goal programming methodology. Theoretical results is illustrated with the help of a numerical.

  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. Application of fuzzy logic approach for landslide susceptibility mapping in Garuwa sub-basin, East Nepal

    Institute of Scientific and Technical Information of China (English)

    Prabin KAYASTHA

    2012-01-01

    Landslide is one of the major natural disasters which cause extensive loss of life and property.During the last three decades,different researchers have developed different methodologies to prepare landslide susceptibility mapping and hazard assessment in the world.The main goal of this paper is to apply a fuzzy logic approach to landslide susceptibility mapping in the Garuwa sub-basin area,East Nepal.Eight different causative factors are considered:slope angle,slope aspect,slope shape,relative relief,distance from drainage,land use,geology,and distance from active faults.Likelihood ratios are obtained for each class of causative factors by comparison with past landslide occurrences.Then,the likelihood ratios are normalized between zero and one to obtain fuzzy membership values.Next,different fuzzy operators are applied to generate landslide susceptibility maps.Comparison with the landslide inventory map reveals that the fuzzy gamma (γ) operator with a γ-value of 0.70 yields the best prediction accuracy which is then used to produce the final landslide susceptibility zonation map.

  11. A generalized fuzzy linear programming approach for environmental management problem under uncertainty.

    Science.gov (United States)

    Fan, Yurui; Huang, Guohe; Veawab, Amornvadee

    2012-01-01

    In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO2) control planning model to identify effective SO2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP and then identify desired policies for SO2-emission control under uncertainty.

  12. Quantification of sand fraction from seismic attributes using Neuro-Fuzzy approach

    Science.gov (United States)

    Verma, Akhilesh K.; Chaki, Soumi; Routray, Aurobinda; Mohanty, William K.; Jenamani, Mamata

    2014-12-01

    In this paper, we illustrate the modeling of a reservoir property (sand fraction) from seismic attributes namely seismic impedance, seismic amplitude, and instantaneous frequency using Neuro-Fuzzy (NF) approach. Input dataset includes 3D post-stacked seismic attributes and six well logs acquired from a hydrocarbon field located in the western coast of India. Presence of thin sand and shale layers in the basin area makes the modeling of reservoir characteristic a challenging task. Though seismic data is helpful in extrapolation of reservoir properties away from boreholes; yet, it could be challenging to delineate thin sand and shale reservoirs using seismic data due to its limited resolvability. Therefore, it is important to develop state-of-art intelligent methods for calibrating a nonlinear mapping between seismic data and target reservoir variables. Neural networks have shown its potential to model such nonlinear mappings; however, uncertainties associated with the model and datasets are still a concern. Hence, introduction of Fuzzy Logic (FL) is beneficial for handling these uncertainties. More specifically, hybrid variants of Artificial Neural Network (ANN) and fuzzy logic, i.e., NF methods, are capable for the modeling reservoir characteristics by integrating the explicit knowledge representation power of FL with the learning ability of neural networks. In this paper, we opt for ANN and three different categories of Adaptive Neuro-Fuzzy Inference System (ANFIS) based on clustering of the available datasets. A comparative analysis of these three different NF models (i.e., Sugeno-type fuzzy inference systems using a grid partition on the data (Model 1), using subtractive clustering (Model 2), and using Fuzzy c-means (FCM) clustering (Model 3)) and ANN suggests that Model 3 has outperformed its counterparts in terms of performance evaluators on the present dataset. Performance of the selected algorithms is evaluated in terms of correlation coefficients (CC), root

  13. 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.

  14. Logaritmic Fuzzy Preference Programming Approach for Evaluating University Ranking Optimization

    Directory of Open Access Journals (Sweden)

    Tenia Wahyuningrum

    2017-05-01

    Full Text Available Assesing quality university’s website trough webometrics is becoming one of many measures in World Class University. To get good grades, so that it can compete with other universities in the world, it needs to be pursued strategies based on the achievement of the perspective of cost (expenses and the condition of the availability and readiness of human resource (HR owned by the institution. Webometrics ranking optimization tailored to the institutional capacity is absolutely necessary, in order to achieve the expected goals effectively and fuel-efficient. Therefore, this paper discussed the application of the Analytical Hierarchy Process with Logarithmic Fuzzy Preference Programming combination proved to covered of the methods FPP on the university web ranking optimization. From the results of sub-criteria weighting based on the perspective of cost and human resources, earned the highest ranking among other factors recommended monitoring the ranking of sites ahrefs (C332 and majesticseo (C331 as well as increasing the number of links from other websites (C321. 

  15. Reducing the subjectivity of intensity estimates. The Fuzzy Set approach

    Energy Technology Data Exchange (ETDEWEB)

    Vannucci, G. [Consiglio Nazionale delle Ricerche, Centro di studi per la Geologia dell' Appennino e delle Catene Perimediterranee, Florence, (Italy); Gasperini, P. [Bologna Univ., Bologna (Italy). Dipt. di Fisica; Ferrari, G. [Storia Geofisica Ambiente, Bologna (Italy)

    2000-08-01

    In this work it has been described a method for the encoding and the computer analysis of the macro seismic effects deduced from historical sources allowing the complete formalization of the process of seismic intensity assessment. It makes use of a multi-criteria decisions-support algorithm, based on the theory of the Fuzzy Sets. Analyzing the texts of the available sources for the 1919 Mugello (M{sub s}=6.2) and 1920 Garfagnana (M{sub s}=6.5) earthquakes, the observed effects are classified independently of any macro seismic scale. Each sentence reported on the sources is decomposed into five syntactic elementary components and represented by a set of alphanumeric codes for further processing by computer codes. This retains the maximum adherence to the original sources and avoids forced interpretations and losses of information due to the need to fit each observed effect to a description of the scale. Moreover, this scheme also allows to gather equivalent effects by reassigning them the same code, and using this new classification in further processing. This procedure could even be useful to define a new macro seismic scale on the basis of a statistical analysis of different effect occurrences.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. FUZZY SATISFYING INTERACTIVE MULTIOBJECTIVE THERMAL POWER DISPATCH: SWT APPROACH

    Institute of Scientific and Technical Information of China (English)

    Lakhwinder SINGH; J.S.DHILLON

    2007-01-01

    In multiobjective optimization,trade-off analysis plays an important role in determining most preferred solution.This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution.In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz.Cost,Nox emission,Sox emission and Cox emission are minimized simultaneously.The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner.Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain.Exploiting fuzzy decision making theory to access the indifference band,interaction with the decision maker is obtained via surrogate worth trade-off (SWT) functions of the objectives.The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space,so the surrogate worth trade-off functions of objectives relate the decision maker's preferences to non-inferior solutions through optimal weight patterns.The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses.Decoupled load flow analysis is performed to find the transmission losses.The validity of the proposed method is demonstrated on 11-bus,17-lines IEEE system,comprising of three generators.

  1. 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.

  2. Prediction of oil palm production using the weighted average of fuzzy sets concept approach

    Science.gov (United States)

    Nugraha, R. F.; Setiyowati, Susi; Mukhaiyar, Utriweni; Yuliawati, Apriliani

    2015-12-01

    Proper planning becomes crucial for decision making in a company. For oil palm producer companies, the prediction of future products realizations is useful and considered in making company's strategies. It is mean that to do the best in predicting is absolute. Until now, to predict the next monthly oil palm productions, the company use simple mean statistics of the latest five-year observations. Lately, imprecision in estimates of oil palm production (overestimate) becomes a problem and the focus of attention in a company. Here we proposed weighted mean approach by using fuzzy concept approach to do estimation and prediction. We obtain that the prediction using fuzzy concept almost always give underestimate of realizations than the simple mean.

  3. 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.

  4. A NEW FUZZY LOGIC BASED SPACE VECTOR MODULATION APPROACH ON DIRECT TORQUE CONTROLLED INDUCTION MOTORS

    Directory of Open Access Journals (Sweden)

    Fatih Korkmaz

    2013-11-01

    Full Text Available The induction motors are indispensable motor types for industrial applications due to its wellknown advantages. Therefore, many kind of control scheme are proposed for induction motors over the past years and direct torque control has gained great importance inside of them due to fast dynamic torque response behavior and simple control structure. This paper suggests a new approach on the direct torque controlled induction motors, Fuzzy logic based space vector modulation, to overcome disadvantages of conventional direct torque control like high torque ripple. In the proposed approach, optimum switching states are calculated by fuzzy logic controller and applied by space vector pulse width modulator to voltage source inverter. In order to test and compare the proposed DTC scheme with conventional DTC scheme simulations, in Matlab/Simulink, have been carried out in different speed and load conditions. The simulation results showed that a significant improvement in the dynamic torque and speed responses when compared to the conventional DTC scheme.

  5. A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

    CERN Document Server

    Malathi, S

    2011-01-01

    Software Cost Estimation with resounding reliability,productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. A new approach has been developed in this paper to estimate software effort for projects represented by categorical or numerical data using reasoning by analogy and fuzzy approach. The existing historical data sets, analyzed with fuzzy logic, produce accurate results in comparison to the data set analyzed with the earlier methodologies.

  6. 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)

  7. A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    S.Malathi

    2011-11-01

    Full Text Available Software Cost Estimation with resounding reliability, productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. A new approach has been developed in this paper to estimate software effort for projects represented by categorical or numerical data using reasoning by analogy and fuzzy approach. The existing historical datasets, analyzed with fuzzy logic, produce accurate results in comparison to the dataset analyzed with the earlier methodologies.

  8. Fuzzy Boundary and Fuzzy Semiboundary

    OpenAIRE

    Athar, M.; Ahmad, B.

    2008-01-01

    We present several properties of fuzzy boundary and fuzzy semiboundary which have been supported by examples. Properties of fuzzy semi-interior, fuzzy semiclosure, fuzzy boundary, and fuzzy semiboundary have been obtained in product-related spaces. We give necessary conditions for fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions. Moreover, fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions have been characterized via fuzzy-derived (resp., fuzz...

  9. 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.

  10. Edge Detection with Neuro-Fuzzy Approach in Digital Synthesis Images

    Directory of Open Access Journals (Sweden)

    Fatma ZRIBI

    2016-04-01

    Full Text Available This paper presents an enhanced Neuro-Fuzzy (NF Approach of edge detection with an analysis of the characteristic of the method. The specificity of our method is an enhancement of the learning database of the diagonal edges compared to the original learning database. The original inspired NF edge detection model uses just one image learning database realized by Emin Yuksel. The tests are accomplished in synthesis images with a noised one of 20% of Gaussian noise.

  11. QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

    OpenAIRE

    2015-01-01

    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 ...

  12. Internal Due Date Assignment in a Wafer Fabrication Factory by an Effective Fuzzy-Neural Approach

    Directory of Open Access Journals (Sweden)

    Toly Chen

    2013-01-01

    Full Text Available Owing to the complexity of the wafer fabrication, the due date assignment of each job presents a challenging problem to the production planning and scheduling people. To tackle this problem, an effective fuzzy-neural approach is proposed in this study to improve the performance of internal due date assignment in a wafer fabrication factory. Some innovative treatments are taken in the proposed methodology. First, principal component analysis (PCA is applied to construct a series of linear combinations of the original variables to form a new variable, so that these new variables are unrelated to each other as much as possible, and the relationship among them can be reflected in a better way. In addition, the simultaneous application of PCA, fuzzy c-means (FCM, and back propagation network (BPN further improved the estimation accuracy. Subsequently, the iterative upper bound reduction (IUBR approach is proposed to determine the allowance that will be added to the estimated job cycle time. An applied case that uses data collected from a wafer fabrication factory illustrates this effective fuzzy-neural approach.

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

    Science.gov (United States)

    Hu, Yan; Wen, Jing-Ya; Li, Xiao-Li; Wang, Da-Zhou; Li, Yu

    2013-10-15

    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.

  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. 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.

  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. Topsy-turvy world of materials

    Directory of Open Access Journals (Sweden)

    George Marsh

    2003-01-01

    Among other strange consequences, the Doppler effect is reversed: a passing EM source would be characterized by falling then rising frequency rather than the other way around, while light from a source coming towards you would be reddened instead of blue-shifted. The Cerenkov effect is similarly reversed, with charged particles passing though a medium emitting light in a cone behind the particle rather than in front. Evanescent waves, with extremely short wavelengths that decay rapidly and never really escape the surface of a normal material, would actually grow in our topsy-turvy medium. In optics, therefore, these waves — less than the wavelength of light and carrying the finest details of an optical image — could be focused along with the normally propagating waves.

  18. 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

  19. Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

    Institute of Scientific and Technical Information of China (English)

    褚菲; 马小平; 王福利; 贾润达

    2015-01-01

    A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator (partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares (PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.

  20. A novel approach to predict surface roughness in machining operations using fuzzy set theory

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2016-01-01

    Full Text Available The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

  1. 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.

  2. A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Saad M. Darwish

    2016-10-01

    Full Text Available Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions. The problem of expanding procedures to handle quantitative data has been attracting the attention of many researchers. The algorithms regularly discretize the attribute fields into sharp intervals, and then implement uncomplicated algorithms established for Boolean attributes. Fuzzy association rules mining approaches are intended to defeat such shortcomings based on the fuzzy set theory. Furthermore, most of the current algorithms in the direction of this topic are based on very tiring search methods to govern the ideal support and confidence thresholds that agonize from risky computational cost in searching association rules. To accelerate quantitative multilevel association rules searching and escape the extreme computation, in this paper, we propose a new genetic-based method with significant innovation to determine threshold values for frequent item sets. In this approach, a sophisticated coding method is settled, and the qualified confidence is employed as the fitness function. With the genetic algorithm, a comprehensive search can be achieved and system automation is applied, because our model does not need the user-specified threshold of minimum support. Experiment results indicate that the recommended algorithm can powerfully generate non-redundant fuzzy multilevel association rules.

  3. Poverty Level of Households: A Multidimensional Approach Based on Fuzzy Mathematics

    Directory of Open Access Journals (Sweden)

    Amitava Chatterjee

    2014-12-01

    Full Text Available In recent years, extensive research jobs have been developed on the definition, measurement and analyzing of poverty. Poverty is a multidimensional phenomenon, thus a number of challenges appears measuring it. The fuzzy set theoretic approach has been used to measure the poverty and to classify the difference between poor and non-poor households. This paper aims at proposing a new methodology to measure the poverty index in fuzzy environment via a two-step membership function. The concept of one poverty line is chalked out first and then a general method is developed to split the poverty index. Linguistic variables are used for the attributes to find the membership values of the households against the attributes and to grade the attributes. The effectiveness and usefulness of the proposed method is numerically illustrated through a case study for rural household people living in remote rural areas of India.

  4. H∞ synchronization of uncertain fractional order chaotic systems: adaptive fuzzy approach.

    Science.gov (United States)

    Lin, Tsung-Chih; Kuo, Chia-Hao

    2011-10-01

    This paper presents a novel adaptive fuzzy logic controller (FLC) equipped with an adaptive algorithm to achieve H(∞) synchronization performance for uncertain fractional order chaotic systems. In order to handle the high level of uncertainties and noisy training data, a desired synchronization error can be attenuated to a prescribed level by incorporating fuzzy control design and H(∞) tracking approach. Based on a Lyapunov stability criterion, not only the performance of the proposed method is satisfying with an acceptable synchronization error level, but also a rather simple stability analysis is performed. The simulation results signify the effectiveness of the proposed control scheme. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Fuzzy MADM Approach for Identification of Key Sectors of Tajikistan Economy

    Institute of Scientific and Technical Information of China (English)

    ASADULLO Abdulhamidov; TANG Bing-yong; LI Dan

    2006-01-01

    The development strategy, focused on the promotion of the efficient and prospective production sectors required for effectively solving social, economic and other problems becomes very important in resource allocation decision making process of developing countries. The structural hierarchy, comprising social, economic, technological and environmental aspects, which is involved in the selection of sectors constructed according to the hierarchical system of objectives. The Fuzzy Multi-attribute Decision Making method is used to rank the sectors by indicating the degree to which an alternative satisfies the global objectives of criteria obtained by aggregation operations in fuzzy environment. By applying the developed approach to defming and identifying the key sectors of an economy, we can rank the aggregated 17 sectors of the Tajikistan economy according to their degree of achievement in satisfying key criteria.

  6. Analysis of machining characteristics in drilling of GFRP composite with application of fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    B.C. Routar

    2013-10-01

    Full Text Available This paper discusses the application of the Taguchi method to optimize the machining parameters for machining of GFRP composite in drilling for individual responses such as thrust force and delamination factor. Moreover, a multi-response performance characteristic is used for optimization of process parameters with application of grey relational analysis. An orthogonal array (L9, grey relational generation, grey relational coefficient and grey – fuzzy grade obtained from the grey relational analysis applied as performance index to solve the optimization problem of drilling parameters for GFRP composite. Taguchi orthogonal array, the signal-to-noise ratio, and the analysis of variance are used to investigate the optimal levels of cutting parameters. The confirmation tests are conducted to verify the results and it is observed that grey-fuzzy approach is efficient in determining the optimal cutting parameters.

  7. A Comparative Holistic Fuzzy Approach for Evaluation of the Chain Performance of Suppliers

    Directory of Open Access Journals (Sweden)

    Ergün Eraslan

    2014-01-01

    Full Text Available The competition between the companies in the dynamic market conditions has made the Supply Chain Management (SCM a more important issue. The companies which have organized their supply chain effectively have obtained more flexibility in their manufacturing processes in addition to delivery of the customer demands. In this study, two different multicriteria decision making algorithms composed of the FAHP and a holistic hybrid method using FTOPSIS were utilized for an electronic company in wholly fuzzy processes. The FAHP is used for determination of the global weights of the factors and the performances of alternative suppliers are evaluated by using both FAHP-based and FAHP-FTOPSIS hybrid methods for synthetic extent values of pairwise comparisons. The sequences of the suppliers differed for the algorithms. The performances of the proposed approaches are quite successful and flexible in a narrow interval. The managerial advantages obtained from the proposed fuzzy algorithms are also analyzed and interpreted.

  8. Fuzzy Approach for Selecting Optimal COTS Based Software Products Under Consensus Recovery Block Scheme

    Directory of Open Access Journals (Sweden)

    P. C. Jha

    2011-01-01

    Full Text Available The cost associated with development of a large and complex software system is formidable. In today's customer driven market, improvement of quality aspects in terms of reliability of the product is also gaining increased importance. But the resources are limited and the manager has to maneuver within a tight schedule. In order to meet these challenges, many organizations are making use of Commercial Off-The-Shelf (COTS software. This paper develops a fuzzy multi objective optimization model approach for selecting the optimal COTS software product among alternatives for each module in the development of modular software system. The problem is formulated for consensus recovery block fault tolerant scheme. In today’s ever changing environment, it is arduous to estimate the precise cost and reliability of software. Therefore, we develop a fuzzy multi objective optimization models for selecting optimal COTS software products. Numerical illustrations are provided to demonstrate the models developed.

  9. Novel fuzzy feedback linearization strategy for control via differential geometry approach.

    Science.gov (United States)

    Li, Tzuu-Hseng S; Huang, Chiou-Jye; Chen, Chung-Cheng

    2010-07-01

    The study investigates a novel fuzzy feedback linearization strategy for control. The main contributions of this study are to construct a control strategy such that the resulting closed-loop system is valid for any initial condition with almost disturbance decoupling performance, and develop the feedback linearization design for some class of nonlinear control systems. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. Once the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control is immediately applied via a human expert's knowledge to improve the convergence rate. One example, which cannot be solved by the first paper on the almost disturbance decoupling problem, is proposed in this paper to exploit the fact that the almost disturbance decoupling and the convergence rate performances are easily achieved by the proposed approach.

  10. 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.

  11. 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.

  12. Location optimization of multiple distribution centers under fuzzy environment

    Institute of Scientific and Technical Information of China (English)

    Yong WANG; Xiao-lei MA; Yin-hai WANG; Hai-jun MAO; Yong ZHANG

    2012-01-01

    Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operational costs.However,it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center.With growing logistics demands,multiple distribution centers become necessary to meet customers' requirements,but few studies have tackled the multiple distribution center locations (MDCLs) problem.This paper presents a comprehensive algorithm to address the MDCLs problem.Fuzzy integration and clustering approach using the improved axiomatic fuzzy set (AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria.Then,technique for order preference by similarity to ideal solution (TOPSIS) is applied for evaluating and selecting the best candidate for each cluster.Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure.Results from a case study in Guiyang,China,reveals that the proposed approach developed in this study outperforms other similar algorithms for MDCLs selection.This new method may easily be extended to address location planning of other types of facilities,including hospitals,fire stations and schools.

  13. Combining non-precise historical information with instrumental measurements for flood frequency estimation: a fuzzy Bayesian approach

    Science.gov (United States)

    Salinas, Jose Luis; Kiss, Andrea; Viglione, Alberto; Blöschl, Günter

    2016-04-01

    Efforts of the historical environmental extremes community during the last decades have resulted in the obtention of long time series of historical floods, which in some cases range longer than 500 years in the past. In hydrological engineering, historical floods are useful because they give additional information which improves the estimates of discharges with low annual exceedance probabilities, i.e. with high return periods, and additionally might reduce the uncertainty in those estimates. In order to use the historical floods in formal flood frequency analysis, the precise value of the peak discharges would ideally be known, but in most of the cases, the information related to historical floods is given, quantitatively, in a non-precise manner. This work presents an approach on how to deal with the non-precise historical floods, by linking the descriptions in historical records to fuzzy numbers representing discharges. These fuzzy historical discharges are then introduced in a formal Bayesian inference framework, taking into account the arithmetics of non-precise numbers modelled by fuzzy logic theory, to obtain a fuzzy version of the flood frequency curve combining the fuzzy historical flood events and the instrumental data for a given location. Two case studies are selected from the historical literature, representing different facets of the fuzziness present in the historical sources. The results from the cases studies are given in the form of the fuzzy estimates of the flood frequency curves together with the fuzzy 5% and 95% Bayesian credibility bounds for these curves. The presented fuzzy Bayesian inference framework provides a flexible methodology to propagate in an explicit way the imprecision from the historical records into the flood frequency estimate, which allows to assess the effect that the incorporation of non-precise historical information can have in the flood frequency regime.

  14. Evaluating Projects Based on Intuitionistic Fuzzy Group Decision Making

    Directory of Open Access Journals (Sweden)

    Babak Daneshvar Rouyendegh

    2012-01-01

    Full Text Available There are various methods regarding project selection in different fields. This paper deals with an actual application of construction project selection, using two aggregation operators. First, the opinion of experts is used in a model of group decision making called intuitionistic fuzzy TOPSIS (IFT. Secondly, project evaluation is formulated by dynamic intuitionistic fuzzy weighted averaging (DIFWA. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers (DMs for rating the importance of criteria and alternatives. A numerical example for project selection is given to clarify the main developed result in this paper.

  15. Fuzzy Approach to Critical Bus Ranking under Normal and Line Outage Contingencies

    CERN Document Server

    Shankar, Shobha

    2011-01-01

    Identification of critical or weak buses for a given operating condition is an important task in the load dispatch centre. It has become more vital in view of the threat of voltage instability leading to voltage collapse. This paper presents a fuzzy approach for ranking critical buses in a power system under normal and network contingencies based on Line Flow index and voltage profiles at load buses. The Line Flow index determines the maximum load that is possible to be connected to a bus in order to maintain stability before the system reaches its bifurcation point. Line Flow index (LF index) along with voltage profiles at the load buses are represented in Fuzzy Set notation. Further they are evaluated using fuzzy rules to compute Criticality Index. Based on this index, critical buses are ranked. The bus with highest rank is the weakest bus as it can withstand a small amount of load before causing voltage collapse. The proposed method is tested on Five Bus Test System.

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

    Directory of Open Access Journals (Sweden)

    Warid Warid

    Full Text Available 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.

  17. A New Approach to Fault Diagnosis of Power Systems Using Fuzzy Reasoning Spiking Neural P Systems

    Directory of Open Access Journals (Sweden)

    Guojiang Xiong

    2013-01-01

    Full Text Available Fault diagnosis of power systems is an important task in power system operation. In this paper, fuzzy reasoning spiking neural P systems (FRSN P systems are implemented for fault diagnosis of power systems for the first time. As a graphical modeling tool, FRSN P systems are able to represent fuzzy knowledge and perform fuzzy reasoning well. When the cause-effect relationship between candidate faulted section and protective devices is represented by the FRSN P systems, the diagnostic conclusion can be drawn by means of a simple parallel matrix based reasoning algorithm. Three different power systems are used to demonstrate the feasibility and effectiveness of the proposed fault diagnosis approach. The simulations show that the developed FRSN P systems based diagnostic model has notable characteristics of easiness in implementation, rapidity in parallel reasoning, and capability in handling uncertainties. In addition, it is independent of the scale of power system and can be used as a reliable tool for fault diagnosis of power systems.

  18. A fuzzy-set-theory-based approach to analyse species membership in DNA barcoding.

    Science.gov (United States)

    Zhang, A-B; Muster, C; Liang, H-B; Zhu, C-D; Crozier, R; Wan, P; Feng, J; Ward, R D

    2012-04-01

    Reliable assignment of an unknown query sequence to its correct species remains a methodological problem for the growing field of DNA barcoding. While great advances have been achieved recently, species identification from barcodes can still be unreliable if the relevant biodiversity has been insufficiently sampled. We here propose a new notion of species membership for DNA barcoding-fuzzy membership, based on fuzzy set theory-and illustrate its successful application to four real data sets (bats, fishes, butterflies and flies) with more than 5000 random simulations. Two of the data sets comprise especially dense species/population-level samples. In comparison with current DNA barcoding methods, the newly proposed minimum distance (MD) plus fuzzy set approach, and another computationally simple method, 'best close match', outperform two computationally sophisticated Bayesian and BootstrapNJ methods. The new method proposed here has great power in reducing false-positive species identification compared with other methods when conspecifics of the query are absent from the reference database.

  19. 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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Jyoti D. Darbari

    2017-01-01

    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.

  2. Enhancing Stud Arc Welding Technique Vai Utilizing FuzzyLogic Approach (FLA

    Directory of Open Access Journals (Sweden)

    Nabeel K. Abid AL-Sahib

    2013-01-01

    Full Text Available A fuzzy logic approach (FLA application in the process of stud arc welding environment was implemented under the condition of fuzziness input data. This paper is composed of the background of FLA, related research work review and points for developing in stud welding manufacturing. Then, it investigates thecase of developingstud arc welding process on the controversial certaintyof available equipment and human skills.Five parameters (welding time, sheet thickness, type of coating, welding current and stud shape were studied.A pair of parameter was selected asiteration whichis welding current and welding time and used for verification corresponding with tensile strength as output results and this willconsider it as schema for other cases.The testing result in the case of crisp (exact value verifyingied the uncertainty value of some criteria selected which open the concept to make the decision making process for some advance cases without implementation. This paper applied the proposed methodology using Matlab program, the graphic user interface (GUI fuzzy tool box for the case study of screw DABOTEKSTUD welding machine, for 6 mm diameter stud. The sheet materials are (K14358 and K52355 according to (USN standards, and the stud materials are (54NiCrMoS6 and 4OCrMnMoS8-6 according to (DIN standards.This given information is very inevitable for the conventional crisp determination of the tensile stress for the particular specimens experimented and also for verifying the tensile test value estimate in the case of changing to a fuzzy value for two of the input variables.

  3. Decision making with fuzzy probability assessments and fuzzy payoff

    Institute of Scientific and Technical Information of China (English)

    Song Yexin; Yin Di; Chen Mianyun

    2005-01-01

    A novel method for decision making with fuzzy probability assessments and fuzzy payoff is presented. The consistency of the fuzzy probability assessment is considered. A fuzzy aggregate algorithm is used to indicate the fuzzy expected payoff of alternatives. The level sets of each fuzzy expected payoff are then obtained by solving linear programming models. Based on a defuzzification function associated with the level sets of fuzzy number and a numerical integration formula (Newton-Cotes formula), an effective approach to rank the fuzzy expected payoff of alternatives is also developed to determine the best alternative. Finally, a numerical example is provided to illustrate the proposed method.

  4. Fuzzy approach to analysis of flood risk based on variable fuzzy sets and improved information diffusion methods

    Directory of Open Access Journals (Sweden)

    Q. Li

    2013-02-01

    Full Text Available The predictive analysis of natural disasters and their consequences is challenging because of uncertainties and incomplete data. The present article studies the use of variable fuzzy sets (VFS and improved information diffusion method (IIDM to construct a composite method. The proposed method aims to integrate multiple factors and quantification of uncertainties within a consistent system for catastrophic risk assessment. The fuzzy methodology is proposed in the area of flood disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The results of the example indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management.

  5. A new synthesis procedure for TOPSIS based on AHP

    Directory of Open Access Journals (Sweden)

    Juan Aguarón-Joven

    2015-01-01

    Full Text Available Vega et al. [1] analizan la influencia que tiene la dependencia entre atributos al ordenar con TOPSIS un conjunto de alternativas en un problema de decisión multicriterio. Asimismo, estos autores proponen utilizar la distancia de Mahalanobis en TOPSIS para incorporar las correlaciones entre los atributos. El problema es que, incluso en situaciones en las que la dependencia entre atributos es muy pequeña, los resultados obtenidos utilizando la distancia de Mahalanobis difieren significativamente de los obtenidos con la distancia euclídea tradicionalmente empleada en TOPSIS, así como de los obtenidos con cualquier otra distancia de la familia de Minkowsky. Este hecho provoca serias dudas a la hora de seleccionar la distancia que debe utilizarse en cada caso. Para abordar el problema de la dependencia entre atributos y el asociado con la selección de la distancia más apropiada, este trabajo propone utilizar una nueva forma de sintetizar las distancias al ideal y anti-ideal en TOPSIS. Este nuevo procedimiento, basado en el Proceso Analítico Jerárquico (AHP, permite capturar la importancia relativa de ambas distancias en el contexto delimitado por la medida considerada y proporciona ordenaciones más cercanas que las de la síntesis tradicional para las diferentes distancias empleadas con TOPSIS, independientemente de la existencia de dependencia entre atributos. El procedimiento propuesto ha sido aplicado al ejemplo seleccionado por Vega et al. [1].

  6. A Generalized Automatic Hybrid Fuzzy-Based GA-PSO Clustering Approach

    Directory of Open Access Journals (Sweden)

    Amir Hooshang Mazinan, ,

    2014-09-01

    Full Text Available The main contribution of the present research arises from developing the traditional methods in the area of segmentation of brain magnetic resonance imaging (MRI. Contemporary research is now developing techniques to solve the whole considerable problems in this field, such as the fuzzy local information c-mean (FLICM approach that incorporate the local spatial and the gray level information. It should be noted that the present approach is robust against noise, although the high computational complexity is not truly ignored. A novel approach in segmentation of brain MRI has been investigated and presented through the proposed research. Because of so many noises embedded in the acquiring procedure, like eddy currents, the segmentation of the brain MR is now tangibly taken into account as a difficult task. Fuzzy-based clustering algorithm is one of the solutions in the same way. But, it is so sensitive to change through noise and other imaging artifacts. The idea of combining the genetic algorithm (GA and particle swarm optimization (PSO for the purpose of generalizing the FLICM is the ultimate goal in the present investigation, since the computational complexity could actually be reduced. The experiments with a number of simulated images as well as the clinical MRI data illustrate that the proposed approach is applicable and effective.

  7. A Ranking Approach for Intuitionistic Fuzzy Numbers and its Application

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2013-06-01

    Full Text Available To the best of our knowledge very few methods have been proposed in previous studies for comparing intuitionisticfuzzy (IF numbers. In this paper, the limitations and the shortcomings of all these existing methods are pointed out. Inorder to overcome these limitations and shortcomings a new ranking approach—by modifying an existing rankingapproach—is proposed for comparing IF numbers. Thus, with the help of proposed the ranking approach, a newmethod is proposed to find the optimal solution of such unbalanced minimum cost flow (MCF problems in which allthe parameters are represented by IF numbers.

  8. Systematic Approach to Formulate PSS Development Project Proposals in the Fuzzy Front End

    DEFF Research Database (Denmark)

    Barquet, Ana Paula B.; Pigosso, Daniela Cristina Antelmi; Rozenfeld, Henrique

    2013-01-01

    patterns adopted for product development. Currently, there is not a systematic approach that can be followed for the formulation of PSS proposals in the fuzzy front end. Therefore, the aim of this research is to develop a method for defining PSS project proposals based on attributes that should...... be considered by companies during this definition. The systematization of PSS attributes may help increase the knowledge about different PSS projects that can emerge in the front end, thus leading to the discovery of opportunities that are not apparent in the existing business models and give rise to new ideas...

  9. 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.

  10. Systematic Approach to Formulate PSS Development Project Proposals in the Fuzzy Front End

    DEFF Research Database (Denmark)

    Barquet, Ana Paula B.; Pigosso, Daniela Cristina Antelmi; Rozenfeld, Henrique

    2013-01-01

    patterns adopted for product development. Currently, there is not a systematic approach that can be followed for the formulation of PSS proposals in the fuzzy front end. Therefore, the aim of this research is to develop a method for defining PSS project proposals based on attributes that should...... be considered by companies during this definition. The systematization of PSS attributes may help increase the knowledge about different PSS projects that can emerge in the front end, thus leading to the discovery of opportunities that are not apparent in the existing business models and give rise to new ideas...

  11. New approach for motion coordination of a mobile manipulator using fuzzy behavioral algorithms

    Science.gov (United States)

    Haeusler, Kurt; Klement, Erich P.; Zeichen, Gerfried

    1998-10-01

    In this paper a new approach for the coordination of the motion axes of a mobile manipulator based on fuzzy behavioral algorithms and its implementation on a physical demonstrator is presented. The kinematic redundancy of the overall system (consisting of a 7 DOF manipulator and a 3 DOF mobile robot) will be used for autonomous and reactive motion of the mobile manipulator within poorly structured and even dynamically changing surroundings. Sensors around the mobile and along the manipulator will provide the necessary information for navigation purposes and perception of the environment.

  12. Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach.

    Science.gov (United States)

    Ahmed, Hameed Kaleel; Zulquernain, Mallick

    2009-01-01

    Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems. Among them, adaptive neuro-fuzzy inference system provides a systematic and directed approach for model building and gives the best possible design parameters in minimum possible time. This study aims to develop a neuro-fuzzy model to predict the effects of noise pollution on human work efficiency as a function of noise level, exposure time, and age of the operators doing complex type of task.

  13. Boolean Operator Fuzzy Logic

    Institute of Scientific and Technical Information of China (English)

    刘叙华; 邓安生

    1994-01-01

    A new approach of operator fuzzy logic, Boolean operator fuzzy logic (BOFL) based on Boolean algebra, is presented. The resolution principle is also introduced into BOFL. BOFL is a natural generalization of classical logic and can be applied to the qualitative description of fuzzy knowledge.

  14. 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.

  15. A fuzzy Bayesian network approach to quantify the human behaviour during an evacuation

    Science.gov (United States)

    Ramli, Nurulhuda; Ghani, Noraida Abdul; Ahmad, Nazihah

    2016-06-01

    Bayesian Network (BN) has been regarded as a successful representation of inter-relationship of factors affecting human behavior during an emergency. This paper is an extension of earlier work of quantifying the variables involved in the BN model of human behavior during an evacuation using a well-known direct probability elicitation technique. To overcome judgment bias and reduce the expert's burden in providing precise probability values, a new approach for the elicitation technique is required. This study proposes a new fuzzy BN approach for quantifying human behavior during an evacuation. Three major phases of methodology are involved, namely 1) development of qualitative model representing human factors during an evacuation, 2) quantification of BN model using fuzzy probability and 3) inferencing and interpreting the BN result. A case study of three inter-dependencies of human evacuation factors such as danger assessment ability, information about the threat and stressful conditions are used to illustrate the application of the proposed method. This approach will serve as an alternative to the conventional probability elicitation technique in understanding the human behavior during an evacuation.

  16. Fuzzy-hybrid land vehicle driveline modelling based on a moving window subtractive clustering approach

    Science.gov (United States)

    Economou, J. T.; Knowles, K.; Tsourdos, A.; White, B. A.

    2011-02-01

    In this article, the fuzzy-hybrid modelling (FHM) approach is used and compared to the input-output system Takagi-Sugeno (TS) modelling approach which correlates the drivetrain power flow equations with the vehicle dynamics. The output power relations were related to the drivetrain bounded efficiencies and also to the wheel slips. The model relates also to the wheel and ground interactions via suitable friction coefficient models relative to the wheel slip profiles. The wheel slip had a significant efficiency contribution to the overall driveline system efficiency. The peak friction slip and peak coefficient of friction values are known a priori during the analysis. Lastly, the rigid body dynamical power has been verified through both simulation and experimental results. The mathematical analysis has been supported throughout the paper via experimental data for a specific electric robotic vehicle. The identification of the localised and input-output TS models for the fuzzy hybrid and the experimental data were obtained utilising the subtractive clustering (SC) methodology. These results were also compared to a real-time TS SC approach operating on periodic time windows. This article concludes with the benefits of the real-time FHM method for the vehicle electric driveline due to the advantage of both the analytical TS sub-model and the physical system modelling for the remaining process which can be clearly utilised for control purposes.

  17. 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.

  18. 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.

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

    Science.gov (United States)

    Sen, Kingshuk; Ghosh, Surojit; Sarkar, Bijan

    2016-06-01

    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. Assessment of Potential Location of High Arsenic Contamination Using Fuzzy Overlay and Spatial Anisotropy Approach in Iron Mine Surrounding Area

    Directory of Open Access Journals (Sweden)

    Thanes Weerasiri

    2014-01-01

    Full Text Available Fuzzy overlay approach on three raster maps including land slope, soil type, and distance to stream can be used to identify the most potential locations of high arsenic contamination in soils. Verification of high arsenic contamination was made by collection samples and analysis of arsenic content and interpolation surface by spatial anisotropic method. A total of 51 soil samples were collected at the potential contaminated location clarified by fuzzy overlay approach. At each location, soil samples were taken at the depth of 0.00-1.00 m from the surface ground level. Interpolation surface of the analysed arsenic content using spatial anisotropic would verify the potential arsenic contamination location obtained from fuzzy overlay outputs. Both outputs of the spatial surface anisotropic and the fuzzy overlay mapping were significantly spatially conformed. Three contaminated areas with arsenic concentrations of 7.19±2.86, 6.60±3.04, and 4.90±2.67 mg/kg exceeded the arsenic content of 3.9 mg/kg, the maximum concentration level (MCL for agricultural soils as designated by Office of National Environment Board of Thailand. It is concluded that fuzzy overlay mapping could be employed for identification of potential contamination area with the verification by surface anisotropic approach including intensive sampling and analysis of the substances of interest.

  1. Assessment of potential location of high arsenic contamination using fuzzy overlay and spatial anisotropy approach in iron mine surrounding area.

    Science.gov (United States)

    Weerasiri, Thanes; Wirojanagud, Wanpen; Srisatit, Thares

    2014-01-01

    Fuzzy overlay approach on three raster maps including land slope, soil type, and distance to stream can be used to identify the most potential locations of high arsenic contamination in soils. Verification of high arsenic contamination was made by collection samples and analysis of arsenic content and interpolation surface by spatial anisotropic method. A total of 51 soil samples were collected at the potential contaminated location clarified by fuzzy overlay approach. At each location, soil samples were taken at the depth of 0.00-1.00 m from the surface ground level. Interpolation surface of the analysed arsenic content using spatial anisotropic would verify the potential arsenic contamination location obtained from fuzzy overlay outputs. Both outputs of the spatial surface anisotropic and the fuzzy overlay mapping were significantly spatially conformed. Three contaminated areas with arsenic concentrations of 7.19 ± 2.86, 6.60 ± 3.04, and 4.90 ± 2.67 mg/kg exceeded the arsenic content of 3.9 mg/kg, the maximum concentration level (MCL) for agricultural soils as designated by Office of National Environment Board of Thailand. It is concluded that fuzzy overlay mapping could be employed for identification of potential contamination area with the verification by surface anisotropic approach including intensive sampling and analysis of the substances of interest.

  2. An Approach to Associative Retrieval through the Theory of Fuzzy Sets

    Science.gov (United States)

    Sachs, Wladimir

    1976-01-01

    The theory of fuzzy sets is used to provide a rigorous formulation of the problem of associative retrieval. This formulation suggests the idea of using fuzzy clustering to organize data for retrieval. (Author)

  3. The TOPSIS Evaluation on Carbon Emission Economic Efficiency

    Institute of Scientific and Technical Information of China (English)

    Sheng; XU; Chao; ZHANG; Juan; YANG

    2013-01-01

    Based on carbon emission data of 17 cities in Shandong Province in 2005-2009,this paper analyzes carbon emission economic efficiency. It conducts weight distribution by the Ordered Weighted Averaging ( OWA) method,and takes systematic evaluation on carbon emission economic efficiency using TOPSIS method. In eastern coastal regions,including Dongying,Yantai,Weihai and Qingdao,the carbon emission economic efficiency is generally higher than inland regions of Shandong Province. The conclusion reached after correction of time weight is basically consistent with traditional TOPSIS overall evaluation,further proves validity of the evaluation. Finally,it gives recommendations for improving carbon emission economic efficiency in Shandong Province.

  4. Novel Approach to Fuzzy Logic Controller Design for Systems With Deadzones

    OpenAIRE

    Kim, Jong-Hwan; Park, Jong-Hwan; Lee, Seon-Woo; Chong, Edwin K. P.

    1992-01-01

    Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. In particular, we show that a conventional fuzzy logic controller applied to a system with a deadzone suffers from poor transient performance and a large steady-state error. In this report, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator...

  5. A new approach for the sequence spaces of fuzzy level sets with the partial metric

    Directory of Open Access Journals (Sweden)

    Uğur Kadak

    2014-03-01

    Full Text Available In this paper, we investigate the classical sets of sequences of fuzzy numbers by using partial metric which is based on a partial ordering. Some elementary notions and concepts for partial metric and fuzzy level sets are given. In addition, several necessary and sufficient conditions for partial completeness are established by means of fuzzy level sets. Finally, we give some illustrative examples and present some results between fuzzy and partial metric spaces.

  6. 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.

  7. 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%.

  8. 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.

  9. Application of probabilistic and fuzzy cognitive approaches in semantic web framework for medical decision support.

    Science.gov (United States)

    Papageorgiou, Elpiniki I; Huszka, Csaba; De Roo, Jos; Douali, Nassim; Jaulent, Marie-Christine; Colaert, Dirk

    2013-12-01

    This study aimed to focus on medical knowledge representation and reasoning using the probabilistic and fuzzy influence processes, implemented in the semantic web, for decision support tasks. Bayesian belief networks (BBNs) and fuzzy cognitive maps (FCMs), as dynamic influence graphs, were applied to handle the task of medical knowledge formalization for decision support. In order to perform reasoning on these knowledge models, a general purpose reasoning engine, EYE, with the necessary plug-ins was developed in the semantic web. The two formal approaches constitute the proposed decision support system (DSS) aiming to recognize the appropriate guidelines of a medical problem, and to propose easily understandable course of actions to guide the practitioners. The urinary tract infection (UTI) problem was selected as the proof-of-concept example to examine the proposed formalization techniques implemented in the semantic web. The medical guidelines for UTI treatment were formalized into BBN and FCM knowledge models. To assess the formal models' performance, 55 patient cases were extracted from a database and analyzed. The results showed that the suggested approaches formalized medical knowledge efficiently in the semantic web, and gave a front-end decision on antibiotics' suggestion for UTI.

  10. 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.

  11. An Agent-Based Fuzzy Collaborative Intelligence Approach for Predicting the Price of a Dynamic Random Access Memory (DRAM Product

    Directory of Open Access Journals (Sweden)

    Toly Chen

    2012-05-01

    Full Text Available Predicting the price of a dynamic random access memory (DRAM product is a critical task to the manufacturer. However, it is not easy to contend with the uncertainty of the price. In order to effectively predict the price of a DRAM product, an agent-based fuzzy collaborative intelligence approach is proposed in this study. In the agent-based fuzzy collaborative intelligence approach, each agent uses a fuzzy neural network to predict the DRAM price based on its view. The agent then communicates its view and forecasting results to other agents with the aid of an automatic collaboration mechanism. According to the experimental results, the overall performance was improved through the agents’ collaboration.

  12. 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.

  13. 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

  14. Web Service Component Reusability Evaluation: A Fuzzy Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    Aditya Pratap Singh

    2016-01-01

    Full Text Available The service oriented architecture supports reusable components. Component reusability is one of the important features while designing web services for reuse. The reusability is an ideal and key factor to improve the quality and production rate of software. It becomes very helpful for quality assurance, if such quality parameters can be quantified. Non functional quality parameters like reusability are not easy to measure and quantify. This paper attempts to quantify reusability using fuzzy multi criteria approach. This approach is considered due to the unpredictable nature of reusability attributes. For the estimation of reusability, the paper identifies 5 key attributes of reusability i.e. Coupling, Interface Complexity, Security, Response Time and Statelessness in context of web service components.

  15. A Framework for Assessing the Software Reusability using Fuzzy Logic Approach for Aspect Oriented Software

    Directory of Open Access Journals (Sweden)

    Pradeep Kumar Singh

    2015-01-01

    Full Text Available Software reusability is very important and crucial attribute to evaluate the system software. Due to incremental growth of software development, the software reusability comes under attention of many researcher and practitioner. It is pretty easier to reuse the software than developing the new software. Software reusability reduces the development time, cost and effort of software product. Software reusability define the depth to which a module can be reused again with very little or no modification. However the prediction of this quality attribute is cumbersome process. Aspect oriented software development is new approach that introduce the concerns to overcome the issues with modular programming and object oriented programming. However many researcher worked on accessing the software reusability on object oriented system but the software reusability of aspect oriented system is not completely explored. This paper explores the various metric that affects the reusability of aspect oriented software and estimate it using fuzzy logic approach.

  16. 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.

  17. 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.

  18. 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.

  19. Extraction of Coastlines with Fuzzy Approach Using SENTINEL-1 SAR Image

    Science.gov (United States)

    Demir, N.; Kaynarca, M.; Oy, S.

    2016-06-01

    Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS) Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the LIDAR points of

  20. 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.

  1. 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

  2. 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.

  3. Enhancing the Long-Term Yield Competitiveness of a Semiconductor Manufacturing Factory Using a Multiobjective Fuzzy Nonlinear Programming Approach

    Directory of Open Access Journals (Sweden)

    Toly Chen

    2013-01-01

    Full Text Available This study proposes a multiobjective fuzzy nonlinear programming (MOFNP approach to enhance the long-term yield competitiveness of a semiconductor manufacturing factory. By modeling the long-term competitiveness of every product in a semiconductor manufacturing plant with the fuzzy correlation coefficient (FCC between time and instantaneous competitiveness, the proposed model considers the various viewpoints when interpreting the overall competitiveness of the semiconductor manufacturing plant in the long-term. All noninferior solutions of the MOFNP solutions are then derived using a systematic procedure. A real example is employed to illustrate the applicability of the proposed methodology.

  4. 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.

  5. A Fuzzy Set-Based Approach for Model-Based Internet-Banking System Security Risk Assessment

    Institute of Scientific and Technical Information of China (English)

    LI Hetian; LIU Yun; HE Dequan

    2006-01-01

    A fuzzy set-based evaluation approach is demonstrated to assess the security risks for Internet-banking System. The Internet-banking system is semi-formally described using Unified Modeling Language (UML) to specify the behavior and state of the system on the base of analyzing the existing qualitative risk assessment methods. And a quantitative method based on fuzzy set is used to measure security risks of the system. A case study was performed on the WEB server of the Internet-banking System using fuzzy-set based assessment algorithm to quantitatively compute the security risk severity. The numeric result also provides a method to decide the most critical component which should arouse the system administrator enough attention to take the appropriate security measure or controls to alleviate the risk severity. The experiments show this method can be used to quantify the security properties for the Internet-banking System in practice.

  6. 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.

  7. On fuzzy sampled-data control of chaotic systems via a time-dependent Lyapunov functional approach.

    Science.gov (United States)

    Wang, Zi-Peng; Wu, Huai-Ning

    2015-04-01

    In this paper, a novel approach to fuzzy sampled-data control of chaotic systems is presented by using a time-dependent Lyapunov functional. The advantage of the new method is that the Lyapunov functional is continuous at sampling times but not necessarily positive definite inside the sampling intervals. Compared with the existing works, the constructed Lyapunov functional makes full use of the information on the piecewise constant input and the actual sampling pattern. In terms of a new parameterized linear matrix inequality (LMI) technique, a less conservative stabilization condition is derived to guarantee the exponential stability for the closed-loop fuzzy sampled-data system. By solving a set of LMIs, the fuzzy sampled-data controller can be easily obtained. Finally, the chaotic Lorenz system and Rössler's system are employed to illustrate the feasibility and effectiveness of the proposed method.

  8. 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.

  9. 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.

  10. Fault Tolerant Controller Design for a Faulty UAV Using Fuzzy Modeling Approach

    Directory of Open Access Journals (Sweden)

    Moshu Qian

    2016-01-01

    Full Text Available We address a fault tolerant control (FTC issue about an unmanned aerial vehicle (UAV under possible simultaneous actuator saturation and faults occurrence. Firstly, the Takagi-Sugeno fuzzy models representing nonlinear flight control systems (FCS for an UAV with unknown disturbances and actuator saturation are established. Then, a normal H-infinity tracking controller is presented using an online estimator, which is introduced to weaken the saturation effect. Based on the normal tracking controller, we propose an adaptive fault tolerant tracking controller (FTTC to solve actuator loss of effectiveness (LOE fault problem. Compared with previous work, this approach developed in our research need not rely on any fault diagnosis unit and is easily applied in engineering. Finally, these results in simulation indicate the efficiency of our presented FTC scheme.

  11. Fuzzy Goal Programming Approach for Integrating Production and Distribution Problem in Milk Supply Chain

    Directory of Open Access Journals (Sweden)

    Touil Achraf

    2016-01-01

    Full Text Available In this paper, a bi-objective mixed integer programming model is proposed to deal with the production-distribution problem found in a dairy company in Morocco. The supply chain containing three echelons: multi-sites, multi-distribution centers and multi-customers. The model seeks to integrate two conflicting simultaneous objectives: maximizing benefit by considering the shelf life of products and the total cost (quantitative objective, including production, storage, and distribution, as well as maximizing the service level (qualitative objective, which relates to providing satisfactory services to customers. This is subject to several technological constraints that typically arise in the dairy industry, such as sequence-dependent changeover time, machine speed and storage capacity. Due to imprecise aspiration levels of goals, an interactive approach is proposed based on fuzzy goal additive variants to find an efficient compromise solution. Numerical results are reported to demonstrate the efficiency and applicability of the proposed model.

  12. 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.

  13. Multi Response Optimization of Laser Micro Marking Process:A Grey- Fuzzy Approach

    Science.gov (United States)

    Shivakoti, I.; Das, P. P.; Kibria, G.; Pradhan, B. B.; Mustafa, Z.; Ghadai, R. K.

    2017-07-01

    The selection of optimal parametric combination for efficient machining has always become a challenging issue for the manufacturing researcher. The optimal parametric combination always provides a better machining which improves the productivity, product quality and subsequently reduces the production cost and time. The paper presents the hybrid approach of Grey relational analysis and Fuzzy logic to obtain the optimal parametric combination for better laser beam micro marking on the Gallium Nitride (GaN) work material. The response surface methodology has been implemented for design of experiment considering three parameters with their five levels. The parameter such as current, frequency and scanning speed has been considered and the mark width, mark depth and mark intensity has been considered as the process response.

  14. 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.

  15. 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

  16. using fuzzy-robust approach for minimizing transportation and fuel costs in location problem under uncertainty

    Directory of Open Access Journals (Sweden)

    hasan hosseini nasab

    2016-02-01

    Full Text Available Operations research is a commonly used method in many subjects nowadays. One applicable domain of operation research is the problem of facility layout and location. In this paper, a new mathematical programing model is developed for an optimal facility location and assignment. The model includes two objective functions. The first one minimizes the total material handling and fixed costs of facility location. Because of the importance of energy and the main role of fossil fuel in transportation, the second objective function, minimizes the total cost of fuel consumption. To consider the real condition in the proposed model, the cost of fuel, is considered to increase stepwise gradually. In the proposed model the coefficients of objective function are considered to be probabilistic and some of constraints to be fuzzy variables. Using a new approach, this model can be changed to a robust model. To prove the applicability of the model, it is examined for a real condition of facility location.

  17. Adjacent Lane Detection and Lateral Vehicle Distance Measurement Using Vision-Based Neuro-Fuzzy Approaches

    Directory of Open Access Journals (Sweden)

    C.F. Wu

    2013-04-01

    Full Text Available The aim of this article attempts to propose an advanced design of driver assistance system which can provide the driver advisable information about the adjacent lanes and approaching lateral vehicles. The experimental vehicle has a camera mounted at the left side rear view mirror which captures the images of adjacent lane. The detection of lane lines is implemented with methods based on image processing techniques. The candidates for lateral vehicle are explored with lane-based transformation, and each one is verified with the characteristics of its length, width, time duration, and height. Finally, the distances of lateral vehicles are estimated with the well-trained recurrent functional neuro-fuzzy network. The system is tested with nine video sequences captured when the vehicle is driving on Taiwan’s highway, and the experimental results show it works well for different road conditions and for multiple vehicles.

  18. Adjacent Lane Detection and Lateral Vehicle Distance Measurement Using Vision-Based Neuro-Fuzzy Approaches

    Directory of Open Access Journals (Sweden)

    C. F. Wu

    2013-03-01

    Full Text Available The aim of this article attempts to propose an advanced design of driver assistance system which can provide thedriver advisable information about the adjacent lanes and approaching lateral vehicles. The experimental vehiclehas a camera mounted at the left side rear view mirror which captures the images of adjacent lane. The detectionof lane lines is implemented with methods based on image processing techniques. The candidates for lateralvehicle are explored with lane-based transformation, and each one is verified with the characteristics of its length,width, time duration, and height. Finally, the distances of lateral vehicles are estimated with the well-trainedrecurrent functional neuro-fuzzy network. The system is tested with nine video sequences captured when thevehicle is driving on Taiwan’s highway, and the experimental results show it works well for different road conditionsand for multiple vehicles.

  19. 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.

  20. Fuzzy multi-criteria decision-making approach with incomplete information based on evidential reasoning

    Institute of Scientific and Technical Information of China (English)

    Jianqiang Wang; Hongyu Zhang; Zhong Zhang

    2010-01-01

    The weights of criteda are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.

  1. Unknown Input Observer Design for Fuzzy Bilinear System: An LMI Approach

    Directory of Open Access Journals (Sweden)

    D. Saoudi

    2012-01-01

    Full Text Available A new method to design a fuzzy bilinear observer (FBO with unknown inputs is developed for a class of nonlinear systems. The nonlinear system is modeled as a fuzzy bilinear model (FBM. This kind of T-S fuzzy model is especially suitable for a nonlinear system with a bilinear term. The proposed fuzzy bilinear observer subject to unknown inputs is developed to ensure the asymptotic convergence of the error dynamic using the Lyapunov method. The proposed design conditions are given in linear matrix inequality (LMI formulation. The paper studies also the problem of fault detection and isolation. An unknown input fuzzy bilinear fault diagnosis observer design is proposed. This work is given for both continuous and discrete cases of fuzzy bilinear models. Illustrative examples are chosen to provide the effectiveness of the given methodology.

  2. Tuning of a TS Fuzzy Output Regulator Using the Steepest Descent Approach and ANFIS

    Directory of Open Access Journals (Sweden)

    Ricardo Tapia-Herrera

    2013-01-01

    Full Text Available The exact output regulation problem for Takagi-Sugeno (TS fuzzy models, designed from linear local subsystems, may have a solution if input matrices are the same for every local linear subsystem. Unfortunately, such a condition is difficult to accomplish in general. Therefore, in this work, an adaptive network-based fuzzy inference system (ANFIS is integrated into the fuzzy controller in order to obtain the optimal fuzzy membership functions yielding adequate combination of the local regulators such that the output regulation error in steady-state is reduced, avoiding in this way the aforementioned condition. In comparison with the steepest descent method employed for tuning fuzzy controllers, ANFIS approximates the mappings between local regulators with membership functions which are not necessary known functions as Gaussian bell (gbell, sigmoidal, and triangular membership functions. Due to the structure of the fuzzy controller, Levenberg-Marquardt method is employed during the training of ANFIS.

  3. The Selection of the Best Control Rule for a Multiple-Load AGV System Using Simulation and Fuzzy MADM in a Flexible Manufacturing System

    Directory of Open Access Journals (Sweden)

    Parham Azimi

    2010-01-01

    Full Text Available Pick up-dispatching problem together with delivery-dispatching problem of a multiple-load automated guided vehicle (AGV system have been studied. By mixing different pick up-dispatching rules, several control strategies (alternatives have been generated and the best control strategy has been determined considering some important criteria such as System Throughput (ST, Mean Flow Time of Parts (MFTP, Mean Tardiness of Parts (MFTP, AGV Idle Time (AGVIT, AGV Travel Full (AGVTF, AGV Travel Empty (AGVTE, AGV Load Time (AGVLT, AGV Unload Time (AGVUT, Mean Queue Length (MQL and Mean Queue Waiting (MQW. For ranking the control strategies, a new framework based on MADM methods including fuzzy MADM and TOPSIS method were developed. Then several simulation experiments which had been based on a flow path layout to find the results were conducted. Finally, by using TOPSIS method, the control strategies were ranked. Furthermore, a similar approach was used for determining the optimal fleet size. The main contribution of this paper is developing a new approach combining the top managers' views in selecting the best control strategy for AGV systems while trying to optimize the fleet size at the mean time by combining MADM, MCDM and simulation methods.

  4. Fuzzy contractibility

    OpenAIRE

    GÜNER, Erdal

    2007-01-01

    Abstract. In this paper, .rstly some fundamental concepts are included re- lating to fuzzy topological spaces. Secondly, the fuzzy connected set is intro- duced. Finally, de.ning fuzzy contractible space, it is shown that X is a fuzzy contractible space if and only if X is fuzzy homotopic equivalent with a fuzzy single-point space.

  5. 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.

  6. Simulation-Based Fuzzy Logic Approach to Assessing the Effect of Project Quality Management on Construction Performance

    Directory of Open Access Journals (Sweden)

    Gilberto A. Corona-Suárez

    2014-01-01

    Full Text Available This paper reports the development of an approach to integrate the appropriate modeling techniques for estimating the effect of project quality management (PQM on construction performance. This modeling approach features a causal structure that depicts the interaction among the PQM factors affecting quality performance in a given construction operation. In addition, it makes use of fuzzy sets and fuzzy logic in order to incorporate the subjectivity and uncertainty implicit in the performance assessment of these PQM factors to discrete-event simulation models. The outcome is a simulation approach that allows experimenting with different performance levels of the PQM practices implemented in a construction project and obtaining the corresponding productivity estimates of the construction operations. These estimates are intended to facilitate the decision making regarding the improvement of a PQM system implemented in a construction project. A case study is used to demonstrate the usefulness of the proposed simulation approach for evaluating diverse performance improvement alternatives for a PQM system.

  7. Decision Making for Third Party Logistics Supplier Selection in Semiconductor Manufacturing Industry: A Nonadditive Fuzzy Integral Approach

    Directory of Open Access Journals (Sweden)

    Bang-Ning Hwang

    2015-01-01

    Full Text Available The semiconductor industry has a unique vertically disintegrated structure that consists of various firms specializing in a narrow range of the value chain. To ensure manufacturing and logistics efficiency, the semiconductor manufacturers considerably rely on 3PL suppliers to achieve supply chain excellence. However, 3PL supplier selection is a complex decision-making process involving multiple selection criteria. The goal of this paper is to identify the key 3PL selection criteria by employing the nonadditive fuzzy integral approach. Unlike the traditional multicriterion decision-making (MCDM methods which often assume independence among criteria and additive importance weights, the nonadditive fuzzy integral is a more effective approach to solve the dependency among criteria, vagueness in information, and essential fuzziness of human judgment. In this paper, we demonstrate an empirical case that employs the nonadditive fuzzy integral to evaluate the importance weight of selection criteria and choose the most appropriate 3PL supplier. The research result can become a valuable reference for manufacturing companies operating in comparable situations. Moreover, the systematic framework presented in this study can be easily extended to the analysis of other decision-making domains.

  8. 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.

  9. Urban land use and land cover classification using the neural-fuzzy inference approach with Formosat-2 data

    Science.gov (United States)

    Chen, Ho-Wen; Chang, Ni-Bin; Yu, Ruey-Fang; Huang, Yi-Wen

    2009-10-01

    This paper presents a neural-fuzzy inference approach to identify the land use and land cover (LULC) patterns in large urban areas with the 8-meter resolution of multi-spectral images collected by Formosat-2 satellite. Texture and feature analyses support the retrieval of fuzzy rules in the context of data mining to discern the embedded LULC patterns via a neural-fuzzy inference approach. The case study for Taichung City in central Taiwan shows the application potential based on five LULC classes. With the aid of integrated fuzzy rules and a neural network model, the optimal weights associated with these achievable rules can be determined with phenomenological and theoretical implications. Through appropriate model training and validation stages with respect to a groundtruth data set, research findings clearly indicate that the proposed remote sensing technique can structure an improved screening and sequencing procedure when selecting rules for LULC classification. There is no limitation of using broad spectral bands for category separation by this method, such as the ability to reliably separate only a few (4-5) classes. This normalized difference vegetation index (NDVI)-based data mining technique has shown potential for LULC pattern recognition in different regions, and is not restricted to this sensor, location or date.

  10. 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.

  11. Fuzzy knowledge management for the semantic web

    CERN Document Server

    Ma, Zongmin; Yan, Li; Cheng, Jingwei

    2014-01-01

    This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the Semantic Web. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge bases in fuzzy databases, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web. The book aims to provide a single record of current research in the fuzzy knowledge representation and reasoning for the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners and graduate students of the Web intelligence and at the same time serve the knowledge and data engineering professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.

  12. E-Commerce Assessment in Fuzzy Situation

    OpenAIRE

    Fasanghari, Mehdi

    2010-01-01

    The main contribution of this paper is proposing a ranking method for assessing the ecommerce under uncertain situations. In fact, combination of fuzzy triangular rubbers, TOPSIS method, and e-commerce indexes is proposed in this paper. Hence we can assess the customer satisfaction of e-commerce, and we run a case study in which the 5 ecommerce websites are assessed with 10 experts of e-commerce who are familiar with the selected websites. Fortunately, all of the experts are pleased of the ob...

  13. Modeling uncertainty in risk assessment: an integrated approach with fuzzy set theory and Monte Carlo simulation.

    Science.gov (United States)

    Arunraj, N S; Mandal, Saptarshi; Maiti, J

    2013-06-01

    Modeling uncertainty during risk assessment is a vital component for effective decision making. Unfortunately, most of the risk assessment studies suffer from uncertainty analysis. The development of tools and techniques for capturing uncertainty in risk assessment is ongoing and there has been a substantial growth in this respect in health risk assessment. In this study, the cross-disciplinary approaches for uncertainty analyses are identified and a modified approach suitable for industrial safety risk assessment is proposed using fuzzy set theory and Monte Carlo simulation. The proposed method is applied to a benzene extraction unit (BEU) of a chemical plant. The case study results show that the proposed method provides better measure of uncertainty than the existing methods as unlike traditional risk analysis method this approach takes into account both variability and uncertainty of information into risk calculation, and instead of a single risk value this approach provides interval value of risk values for a given percentile of risk. The implications of these results in terms of risk control and regulatory compliances are also discussed.

  14. 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.

  15. A neural learning approach for adaptive image restoration using a fuzzy model-based network architecture.

    Science.gov (United States)

    Wong, H S; Guan, L

    2001-01-01

    We address the problem of adaptive regularization in image restoration by adopting a neural-network learning approach. Instead of explicitly specifying the local regularization parameter values, they are regarded as network weights which are then modified through the supply of appropriate training examples. The desired response of the network is in the form of a gray level value estimate of the current pixel using weighted order statistic (WOS) filter. However, instead of replacing the previous value with this estimate, this is used to modify the network weights, or equivalently, the regularization parameters such that the restored gray level value produced by the network is closer to this desired response. In this way, the single WOS estimation scheme can allow appropriate parameter values to emerge under different noise conditions, rather than requiring their explicit selection in each occasion. In addition, we also consider the separate regularization of edges and textures due to their different noise masking capabilities. This in turn requires discriminating between these two feature types. Due to the inability of conventional local variance measures to distinguish these two high variance features, we propose the new edge-texture characterization (ETC) measure which performs this discrimination based on a scalar value only. This is then incorporated into a fuzzified form of the previous neural network which determines the degree of membership of each high variance pixel in two fuzzy sets, the EDGE and TEXTURE fuzzy sets, from the local ETC value, and then evaluates the appropriate regularization parameter by appropriately combining these two membership function values.

  16. A structured modeling approach for dynamic hybrid fuzzy-first principles models

    NARCIS (Netherlands)

    Lith, van Pascal F.; Betlem, Ben H.L.; Roffel, Brian

    2002-01-01

    Hybrid fuzzy-first principles models can be attractive if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented with fuzzy submodels describing additional equations, such as mass transformation and transfer rate

  17. An Adaptive Fuzzy Control Approach for the Robust Tracking of a MEMS Gyroscope Sensor

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2011-11-01

    Full Text Available In this paper, a direct adaptive fuzzy control using a supervisory compensator is designed for the robust tracking of a MEMS gyroscope sensor. The parameters of the membership functions are adjusted according to the designed adaptive law for the purpose of tracking a reference trajectory. A fuzzy controller that can approximate the unknown nonlinear function and compensate the system

  18. A Fixed Point Approach to the Fuzzy Stability of a Mixed Typ e Functional Equation

    Institute of Scientific and Technical Information of China (English)

    Cheng Li-hua; Zhang Jun-min

    2016-01-01

    Through the paper, a general solution of a mixed type functional equation in fuzzy Banach space is obtained and by using the fixed point method a generalized Hyers-Ulam-Rassias stability of the mixed type functional equation in fuzzy Banach space is proved.

  19. 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-...

  20. 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…

  1. Risk Evaluation Approach and Application Research on Fuzzy-FMECA Method Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Zhengjie Xu

    2013-09-01

    Full Text Available In order to safeguard the safety of passengers and reducemaintenance costs, it is necessary to analyze and evaluate the security risk ofthe Railway Signal System. However, the conventional Fuzzy Analytical HierarchyProcess (FAHP can not describe the fuzziness and randomness of the judgment,accurately, and once the fuzzy sets are described using subjection degreefunction, the concept of fuzziness will be no longer fuzzy. Thus Fuzzy-FMECAmethod based on cloud model is put forward. Failure Modes Effects andCriticality Analysis (FMECA method is used to identify the risk and FAHP basedon cloud model is used for determining the subjection degree function in fuzzymethod, finally the group decision can be gained with the syntheticallyaggregated cloud model, the method’s feasibility and effectiveness are shown inthe practical examples. Finally Fuzzy-FMECA based on cloud model and theconventional FAHP are used to assess the risk respectively, evaluation resultsshow that the cloud model which is introduced into the risk assessment ofRailway Signal System can realize the transition between precise value andquality value by combining the fuzziness and randomness and provide moreabundant information than subjection degree function of the conventional FAHP.

  2. A Fuzzy Set Approach to Modifiers and Vagueness in Natural Language

    Science.gov (United States)

    Hersh, Harry M.; Caramazza, Alfonso

    1976-01-01

    The proposition that natural language concepts are represented as fuzzy sets, a generalization of the traditional theory of sets, of meaning components and that language operators--adverbs, negative markers, and adjectives--can be considered as operators on fuzzy sets was assessed empirically. (Editor/RK)

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

    Science.gov (United States)

    Khan, Faiz Muhammad; Sarmin, Nor Haniza; Khan, Hidayat Ullah

    2014-01-01

    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. PMID:24883375

  4. TOPSIS Method for Determining The Priority of Strategic Training Program

    Directory of Open Access Journals (Sweden)

    Rohmatulloh Rohmatulloh

    2014-01-01

    Full Text Available The voice of stakeholders is an important issue for government or public organizations. The issue becomes an input in designing strategic program. Decision maker should evaluate the priority to get the importance level. The decision making process is a complex problem because it is influenced by many critetria. The purpose of this study is to solve multi-criteria decision making problem using TOPSIS method. This method is proposed due to its easy and simple computation process. The case sample is determining the strategic training program in energy and mineral resources field. TOPSIS analysis may be able to assist decision maker in allocating resources for the preparation of strategic training program in accordance with the priorities

  5. EXTRACTION OF COASTLINES WITH FUZZY APPROACH USING SENTINEL-1 SAR IMAGE

    Directory of Open Access Journals (Sweden)

    N. Demir

    2016-06-01

    Full Text Available Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the

  6. Two Examples of Application of TOPSIS to Decision Making Problems

    Directory of Open Access Journals (Sweden)

    KROHLING, R. A.

    2011-12-01

    Full Text Available In this work, we apply the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS to two case studies. The first example is concerned with the evaluation of the best response alternatives in case of accidental oil spill in the sea. The second example considers the rental evaluation of residential properties. Simulations results are promising and show the feasibility of the technique.

  7. Gestão do desempenho em cadeias de suprimentos usando lógica fuzzy A fuzzy logic approach to supply chain performance management

    Directory of Open Access Journals (Sweden)

    Gilberto Miller Devós Ganga

    2011-01-01

    Full Text Available Este trabalho apresenta e discute uma proposta baseada na teoria dos conjuntos fuzzy para predizer o desempenho de uma cadeia de suprimentos modelada de acordo com os relacionamentos causais entre medidas de desempenho propostas pelo SCOR (versão 8.0. O uso de sistemas de medição de desempenho para gerenciar o desempenho de cadeias de suprimentos apresenta algumas limitações tais como a dificuldade de interpretação de resultados de natureza qualitativa, assim como a complexidade de um sistema tradicional de medição de desempenho lidar adequadamente com os relacionamentos causais entre métricas de desempenho de diferentes processos de negócios ao longo da cadeia de suprimentos. Por outro lado, a Lógica Fuzzy, uma técnica apropriada para lidar com situações de incerteza e subjetividade, configura-se como uma alternativa interessante. Utilizando uma abordagem de pesquisa quantitativa descritiva, assumiu-se a hipótese de que um modelo de predição quantitativo poderia ser construído para explicar (no mínimo em parte o comportamento de processos operacionais. Os resultados do modelo mostraram-se bastante consistentes à metodologia SCOR mark, proposta pelo Supply Chain Council. Análises estatísticas dos resultados, baseados no Método de Superfície de Resposta, também confirmaram a relevância dos relacionamentos causais incorporados no modelo. Em geral, os resultados reforçam que a proposição da adoção de um modelo de predição baseado em lógica fuzzy e nas métricas do SCOR parece ser uma abordagem possível para auxiliar os gerentes no processo de tomada de decisão do gerenciamento do desempenho em cadeias de suprimentos.Supply chain measurement is a complex activity due to the broad taxonomy of variables (quantitative or qualitative; financial or non-financial, and others. This scenario results in a vague and subjective process to evaluate performance. Accordingly, the fuzzy logic seems to be a viable approach to

  8. Design of Fuzzy Controllers

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre- and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based...... on an international standard which is underway. The paper contains also a design approach, which uses a PID controller as a starting point. A design engineer can view the paper as an introduction to fuzzy controller design....

  9. Using the Fuzzy Linguistic Preference Relation Approach for Assessing the Importance of Risk Factors in a Software Development Project

    Directory of Open Access Journals (Sweden)

    Shih-Tong Lu

    2013-01-01

    Full Text Available This study employs fuzzy linguistic preference relation (Fuzzy LinPreRa approach to assess the relative degree of impact of risk factors in software development project for two expert groups working in technology enterprises and software development companies. For the identified risk dimensions, the results show the same rankings for these two groups. “Organization function risk” is considered the most important dimension influencing the software development project performance, with the others, in order, being “developing technology risk,” “resources integration risk,” “personnel system risk” and “system requirement risk.” The proposed approach not only facilitates the information collecting for making pairwise comparisons, but it also eliminates the inconsistencies in the collected information.

  10. 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.

  11. a Fuzzy Logic-Based Approach for the Detection of Flooded Vegetation by Means of Synthetic Aperture Radar Data

    Science.gov (United States)

    Tsyganskaya, V.; Martinis, S.; Twele, A.; Cao, W.; Schmitt, A.; Marzahn, P.; Ludwig, R.

    2016-06-01

    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.

  12. 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.

  13. A unified approach to fuzzy modelling and robust synchronization of different hyperchaotic systems

    Institute of Scientific and Technical Information of China (English)

    Zhang Hua-Guang; Zhao Yan; Yu Wen; Yang Dong-Sheng

    2008-01-01

    In this paper,a Takagi-Sugeno (T-S) fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems.The T-S fuzzy models with a small number of fuzzy IF-THEN rules are employed to represent many typical hyperchaotic systems exactly.The benefit of employing the T-S fuzzy models lies in mathematical simplicity of analysis.Based on the T-S fuzzy hyperchaotic models,two fuzzy controllers are designed via parallel distributed compensation (PDC) and exact linearization (EL) techniques to synchronize two identical hyperchaotic systems with uncertain parameters and two different hyperchaotic systems,respectively.The sufficient conditions for the robust synchronization of two identical hyperchaotic systems with uncertain parameters and the asymptotic synchronization of two different hyperchaotic systems are derived by applying the Lyapunov stability theory.This method is a universal one of synchronizing two identical or different hyperchaotic systems.Numerical examples are given to demonstrate the validity of the proposed fuzzy model and hyperchaotic synchronization scheme.

  14. Coronary Artery Disease Detection Using a Fuzzy-Boosting PSO Approach

    Directory of Open Access Journals (Sweden)

    N. Ghadiri Hedeshi

    2014-01-01

    Full Text Available In the past decades, medical data mining has become a popular data mining subject. Researchers have proposed several tools and various methodologies for developing effective medical expert systems. Diagnosing heart diseases is one of the important topics and many researchers have tried to develop intelligent medical expert systems to help the physicians. In this paper, we propose the use of PSO algorithm with a boosting approach to extract rules for recognizing the presence or absence of coronary artery disease in a patient. The weight of training examples that are classified properly by the new rules is reduced by a boosting mechanism. Therefore, in the next rule generation cycle, the focus is on those fuzzy rules that account for the currently misclassified or uncovered instances. We have used coronary artery disease data sets taken from University of California Irvine, (UCI, to evaluate our new classification approach. Results show that the proposed method can detect the coronary artery disease with an acceptable accuracy. Also, the discovered rules have significant interpretability as well.

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

    Directory of Open Access Journals (Sweden)

    Abass Samir A.

    2007-01-01

    Full Text Available 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. .

  16. Optimality test in fuzzy inventory model for restricted budget and space: Move forward to a non-linear programming approach

    Directory of Open Access Journals (Sweden)

    Pattnaik Monalisha

    2015-01-01

    Full Text Available In this paper, the concept of fuzzy Non-Linear Programming Technique is applied to solve an economic order quantity (EOQ model for restricted budget and 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 the usual probabilistic models. The questions are how to define inventory optimization tasks in such environment and how to interpret the optimal solutions. This paper allow 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. The modification of objective function, budget, and storage area in the presence of imprecisely estimated parameters are considered. The model is developed by employing different approaches over an infinite planning horizon. It incorporates all the concepts of a fuzzy arithmetic approach and comparative analysis with other non linear models. Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated by an example problem, and two and three dimensional diagrams are represented to this application through MATL(R2009a software. Sensitivity analysis of the optimal solution is studied with respect to the changes of different parameter values for obtaining managerial insights of the decision problem.

  17. 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.

  18. 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.

  19. Mathematics of Fuzzy Sets and Fuzzy Logic

    CERN Document Server

    Bede, Barnabas

    2013-01-01

    This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic.   Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage. The main purpose of the present book is to reduce this gap by providing a theoretical introduction into Fuzzy Sets based on Mathematical Analysis and Approximation Theory. Well-known applications, as for example fuzzy control, are also discussed in this book and placed on new ground, a theoretical foundation. Moreover, a few advanced chapters and several new results are included. These comprise, among others, a new systematic and constructive approach for fuzzy infer...

  20. A polynomial response surface approach for the solution of fuzzy elliptic partial differential equations

    OpenAIRE

    Corveleyn, Samuel; Vandewalle, Stefan

    2011-01-01

    Uncertain parameters in mathematical models of physical phenomena are typically modeled by means of random numbers, random fields or random processes. If these uncertainties are of the epistemic kind, calculations with random parameters can lead to very unexpected and unreliable results. Fuzzy set theory was introduced as an alternative to probability theory for a better modeling of epistemic uncertainty. We consider the solution of elliptic partial differential equations with a fuzzy diffus...

  1. 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.

  2. Prediction of Software Requirements Stability Based on Complexity Point Measurement Using Multi-Criteria Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    D. Francis Xavier Christopher

    2012-12-01

    Full Text Available Many software projects fail due to instable requirements and lack of managing the requirements changesefficiently. Software Requirements Stability Index Metric (RSI helps to evaluate the overall stability ofrequirements and also keep track of the project status. Higher the stability, less changes tends topropagate. The existing system use Function Point modeling for measuring the Requirements Stability.However, the main drawback of the existing modeling is that the complexity of non-functional requirementshas not been measured for Requirements Stability. The Non-Functional Factors plays a vital role inassessing the Requirements Stability. Numerous Measurement methods have been proposed for measuringthe software complexity. This paper proposes Multi-criteria Fuzzy Based approach for finding out thecomplexity weight based on Requirement Complexity Attributes such as Functional RequirementComplexity, Non-Functional Requirement Complexity, Input Output Complexity, Interface and FileComplexity. Based on the complexity weight, this paper computes the software complexity point. And thenpredict the Software Requirements Stability based on Software Complexity Point changes. The advantageof this model is that it is able to estimate the software complexity early which in turn predicts the SoftwareRequirement Stability during the software development life cycle.

  3. 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.

  4. A Fuzzy Color-Based Approach for Understanding Animated Movies Content in the Indexing Task

    Directory of Open Access Journals (Sweden)

    Buzuloiu Vasile

    2008-01-01

    Full Text Available Abstract 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.

  5. A transfer learning framework for traffic video using neuro-fuzzy approach

    Indian Academy of Sciences (India)

    P M ASHOK KUMAR; V VAIDEHI

    2017-09-01

    One of the main challenges in the Traffic Anomaly Detection (TAD) system is the ability to deal with unknown target scenes. As a result, the TAD system performs less in detecting anomalies. This paper introduces a novelty in the form of Adaptive Neuro-Fuzzy Inference System-Lossy-Count-based Topic Extraction (ANFIS-LCTE) for classification of anomalies in source and target traffic scenes. The process of transforming the input variables, learning the semantic rules in source scene and transferring the model to target scene achieves the transfer learning property. The proposed ANFIS-LCTE transfer learning model consists offour steps. (1) Low level visual items are extracted only for motion regions using optical flow technique. (2)Temporal transactions are created using aggregation of visual items for each set of frames. (3) An LCTE is applied for each set of temporal transaction to extract latent sequential topics. (4) ANFIS training is done with the back-propagation gradient descent method. The proposed ANFIS model framework is tested on standard dataset and performance is evaluated in terms of training performance and classification accuracies. Experimental results confirm that the proposed ANFIS-LCTE approach performs well in both source and targetdatasets.

  6. Ozone prediction based on meteorological variables: a fuzzy inductive reasoning approach

    Directory of Open Access Journals (Sweden)

    A. Nebot

    2008-06-01

    Full Text Available MILAGRO project was conducted in Mexico City during March 2006 with the main objective of study the local and global impact of pollution generated by megacities. The research presented in this paper is framed in MILAGRO project and is focused on the study and development of modeling methodologies that allow the forecasting of daily ozone concentrations. The present work aims to develop Fuzzy Inductive Reasoning (FIR models using the Visual-FIR platform. FIR offers a model-based approach to modeling and predicting either univariate or multivariate time series. Visual-FIR offers an easy-friendly environment to perform this task. In this research, long term prediction of maximum ozone concentration in the downtown of Mexico City Metropolitan Area is performed. The data were registered every hour and include missing values. Two modeling perspectives are analyzed, i.e. monthly and seasonal models. The results show that the developed models are able to predict the diurnal variation of ozone, including its maximum daily value in an accurate manner.

  7. 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.

  8. 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.

  9. A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2015-12-01

    Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environment and the acquired condition monitoring data are usually noisy and subject to a high level of uncertainty/unpredictability, which complicates prognostics. The complexity further increases, when there is absence of prior knowledge about ground truth (or failure definition). For such issues, data-driven prognostics can be a valuable solution without deep understanding of system physics. This paper contributes a new data-driven prognostics approach namely, an "enhanced multivariate degradation modeling," which enables modeling degrading states of machinery without assuming a homogeneous pattern. In brief, a predictability scheme is introduced to reduce the dimensionality of the data. Following that, the proposed prognostics model is achieved by integrating two new algorithms namely, the summation wavelet-extreme learning machine and subtractive-maximum entropy fuzzy clustering to show evolution of machine degradation by simultaneous predictions and discrete state estimation. The prognostics model is equipped with a dynamic failure threshold assignment procedure to estimate RUL in a realistic manner. To validate the proposition, a case study is performed on turbofan engines data from PHM challenge 2008 (NASA), and results are compared with recent publications.

  10. Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system

    Energy Technology Data Exchange (ETDEWEB)

    Sabahi, Kamel; Teshnehlab, Mohammad; Shoorhedeli, Mahdi Aliyari [Department of Electrical Engineering, K.N. Toosi University of Technology, Intelligent System Lab, Tehran (Iran)

    2009-04-15

    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. (author)

  11. 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.

  12. 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.

  13. Multimodal processes optimization subject to fuzzy operation time constraints:declarative modeling approach#

    Institute of Scientific and Technical Information of China (English)

    Izabela NIELSEN; Robert WJCIK; Grzegorz BOCEWICZ; Zbigniew BANASZAK

    2016-01-01

    We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle (AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network (MTN). The multimodal processes behind the multi-product pro-duction flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN’s structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation (CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.

  14. 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. PMID:26881269

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A new fuzzy edge detection algorithm

    Institute of Scientific and Technical Information of China (English)

    SunWei; XiaLiangzheng

    2003-01-01

    Based upon the maximum entropy theorem of information theory, a novel fuzzy approach for edge detection is presented. Firsdy, a definition of fuzzy partition entropy is proposed after introducing the concepts of fuzzy probability and fuzzy partition. The relation of the probability partition and the fuzzy c-partition of the image gradient are used in the algorithm. Secondly, based on the conditional probabilities and the fuzzy partition, the optimal thresholding is searched adaptively through the maximum fuzzy entropy principle, and then the edge image is obtained. Lastly, an edge-enhancing procedure is executed on the edge image. The experimental results show that the proposed approach performs well.

  2. Selecting Proper Plant Species for Mine Reclamation Using Fuzzy AHP Approach (Case Study: Chadormaloo Iron Mine of Iran)

    Science.gov (United States)

    Ebrahimabadi, Arash

    2016-12-01

    This paper describes an effective approach to select suitable plant species for reclamation of mined lands in Chadormaloo iron mine which is located in central part of Iran, near the city of Bafgh in Yazd province. After mine's total reserves are excavated, the mine requires to be permanently closed and reclaimed. Mine reclamation and post-mining land-use are the main issues in the phase of mine closure. In general, among various scenarios for mine reclamation process, i.e. planting, agriculture, forestry, residency, tourist attraction, etc., planting is the oldest and commonly-used technology for the reclamation of lands damaged by mining activities. Planting and vegetation play a major role in restoring productivity, ecosystem stability and biological diversity to degraded areas, therefore the main goal of this research work is to choose proper and suitable plants compatible with the conditions of Chadormaloo mined area, providing consistent conditions for future use. To ensure the sustainability of the reclaimed landscape, the most suitable plant species adapted to the mine conditions are selected. Plant species selection is a Multi Criteria Decision Making (MCDM) problem. In this paper, a fuzzy MCDM technique, namely Fuzzy Analytic Hierarchy Process (FAHP) is developed to assist chadormaloo iron mine managers and designers in the process of plant type selection for reclamation of the mine under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The results achieved from using FAHP approach demonstrate that the most proper plant species are ranked as Artemisia sieberi, Salsola yazdiana, Halophytes types, and Zygophyllum, respectively for reclamation of Chadormaloo iron mine.

  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. Prediction of Draft Force and Energy Requirement for Subsoiling Operation with a Fuzzy Logic Approach

    Directory of Open Access Journals (Sweden)

    Y Abbaspour Gilandeh

    2013-09-01

    Full Text Available In this study, a knowledge-based fuzzy logic system was developed on experimental data and used to predict the draft force and energy requirement of tillage operation. In comparison with traditional methods, the fuzzy logic model acts more effectively in creating a relationship between multiple inputs to achieve an output signal in a nonlinear range. Field experiments were carried out in a sandy loam soil on coastal plain at the Edisto Research and Education Center of Clemson University near Blackville, South Carolina (Latitude 33˚ 21"N, Longitude 81˚ 18"W. In this paper, a fuzzy model based on Mamdani inference system has been used. This model was developed for predicting the changes of draft force and energy requirement for subsoiling operation. This fuzzy model contains 25 rules. In this investigation, the Mamdani Max-Min inference was used for deducing the mechanism (composition of fuzzy rules with input. The center of gravity defuzzification method was also used for conversion of the final output of the system into a classic number. The validity of the presented model was achieved by numerical error criterion, based on empirical data. The prediction results showed a close relationship between measured and predicted values such that the mean relative error of measured and predicted values were 3.1% and 2.94% for draft resistant force and energy required for subsoiling operation, respectively. The comparison between the fuzzy logic model and the regression models showed that the mean relative errors from the regression model are greater than that from the fuzzy logic model.

  5. Comprehensive Teacher Evaluation Based on Improved TOPSIS Method%基于改进TOPSIS法的教师评价分析

    Institute of Scientific and Technical Information of China (English)

    赵晓燕; 余伟

    2012-01-01

    On the basis of analyzing current teacher evaluation method,this paper presented a teacher evaluation method based on improved TOPSIS method in combination with the theory about fuzzy mathematics,information entropy and multi-objective decision.Fuzzy mathematical method was used to quantify the fuzziness of attribute values,and the information entropy weight method was used to determine the attribute weights,so the influence of subjective preferences on weight distribution was solved preferably.Finally,TOPSIS method combined with multi-objective decision method solved the problem of comprehensive teacher evaluation.It showed that the method was feasible through case studies,and could better reflect the objective,impartial and effective of the evaluation.%在对现有的教师评价方法进行分析的基础上,结合模糊数学、信息熵、多目标决策相关理论提出一种基于改进的TOPSIS法的教师综合评价方法。文章用模糊数学的方法量化了具有模糊性的属性值,运用信息熵权法确定属性权重,较好地解决了权重分配受主观偏好影响的这一问题,最后结合多目标决策中的TOPSIS法对教师综合评价这一问题进行了求解。通过实例分析,证明该方法是切实可行的,能较好地体现评价的客观性、公正性和实效性。

  6. Knowledge-based systems as decision support tools in an ecosystem approach to fisheries: Comparing a fuzzy-logic and rule-based approach

    DEFF Research Database (Denmark)

    Jarre, Astrid; Paterson, B.; Moloney, C.L.

    2008-01-01

    In an ecosystem approach to fisheries (EAF), management must draw on information of widely different types, and information addressing various scales. Knowledge-based systems assist in the decision-making process by summarising this information in a logical, transparent and reproducible way. Both...... decision support tools in our evaluation of the two approaches. With respect to the model objectives, no method clearly outperformed the other. The advantages of numerically processing continuous variables, and interpreting the final output. as in fuzzy-logic models, can be weighed up against...... the advantages of using a few, qualitative, easy-to-understand categories as in rule-based models. The natural language used in rule-based implementations is easily understood by, and communicated among, users of these systems. Users unfamiliar with fuzzy-set theory must "trust" the logic of the model. Graphical...

  7. A Generalized Fuzzy Integer Programming Approach for Environmental Management under Uncertainty

    Directory of Open Access Journals (Sweden)

    Y. R. Fan

    2014-01-01

    Full Text Available In this study, a generalized fuzzy integer programming (GFIP method is developed for planning waste allocation and facility expansion under uncertainty. The developed method can (i deal with uncertainties expressed as fuzzy sets with known membership functions regardless of the shapes (linear or nonlinear of these membership functions, (ii allow uncertainties to be directly communicated into the optimization process and the resulting solutions, and (iii reflect dynamics in terms of waste-flow allocation and facility-capacity expansion. A stepwise interactive algorithm (SIA is proposed to solve the GFIP problem and generate solutions expressed as fuzzy sets. The procedures of the SIA method include (i discretizing the membership function grade of fuzzy parameters into a set of α-cut levels; (ii converting the GFIP problem into an inexact mixed-integer linear programming (IMILP problem under each α-cut level; (iii solving the IMILP problem through an interactive algorithm; and (iv approximating the membership function for decision variables through statistical regression methods. The developed GFIP method is applied to a municipal solid waste (MSW management problem to facilitate decision making on waste flow allocation and waste-treatment facilities expansion. The results, which are expressed as discrete or continuous fuzzy sets, can help identify desired alternatives for managing MSW under uncertainty.

  8. An optimal fuzzy PID control approach for docking maneuver of two spacecraft: Orientational motion

    Directory of Open Access Journals (Sweden)

    A. Kosari

    2017-02-01

    Full Text Available This paper describes a scheme for a Fuzzy-Proportional Integral Derivative (FPID controller based on genetic algorithm (GA, in a docking maneuver of two spacecraft. The docking maneuver consists of two parts: translation and orientation. Euler’s gyroscopic equation is applied to obtain governing equations of orientational phase. Here, a designed fuzzy-PID controller for stabilization purpose of orientational phase of a docking maneuver is presented based on the Single Input Fuzzy Inference Motor (SIFIMs dynamically connected Preferrer Fuzzy Inference Motor (PFIM. This fuzzy-PID controller takes the error signal of Euler’s angles and the error of angular velocities of the chaser as its input items, and the driving force as its output. The parameters of the controller are ascertained by using a genetic algorithm. Conflicting objective functions (which their 3D pareto frontiers are obtained by Multi-objective Genetic Algorithm (MOGA are distance errors from the set point, angle errors from the set point, and control efforts. Optimization constraint is maximal of the momentum produced by momentum wheels. The result of optimum point demonstrates that the designed controller makes an efficient performance in the orientational phase of the chaser spacecraft. Compared to similar works, some of system parameters like settling time are improved and overshoot (as a critical parameter in docking maneuver is decreased.

  9. Distributed Proportional-spatial Derivative control of nonlinear parabolic systems via fuzzy PDE modeling approach.

    Science.gov (United States)

    Wang, Jun-Wei; Wu, Huai-Ning; Li, Han-Xiong

    2012-06-01

    In this paper, a distributed fuzzy control design based on Proportional-spatial Derivative (P-sD) is proposed for the exponential stabilization of a class of nonlinear spatially distributed systems described by parabolic partial differential equations (PDEs). Initially, a Takagi-Sugeno (T-S) fuzzy parabolic PDE model is proposed to accurately represent the nonlinear parabolic PDE system. Then, based on the T-S fuzzy PDE model, a novel distributed fuzzy P-sD state feedback controller is developed by combining the PDE theory and the Lyapunov technique, such that the closed-loop PDE system is exponentially stable with a given decay rate. The sufficient condition on the existence of an exponentially stabilizing fuzzy controller is given in terms of a set of spatial differential linear matrix inequalities (SDLMIs). A recursive algorithm based on the finite-difference approximation and the linear matrix inequality (LMI) techniques is also provided to solve these SDLMIs. Finally, the developed design methodology is successfully applied to the feedback control of the Fitz-Hugh-Nagumo equation.

  10. Using Fuzzy Multiple Criteria Decision-Making Approach for Assessing the Risk of Railway Reconstruction Project in Taiwan

    Science.gov (United States)

    Yu, Shih-Heng; Chang, Dong-Shang

    2014-01-01

    This study investigates the risk factors in railway reconstruction project through complete literature reviews on construction project risks and scrutinizing experiences and challenges of railway reconstructions in Taiwan. Based on the identified risk factors, an assessing framework based on the fuzzy multicriteria decision-making (fuzzy MCDM) approach to help construction agencies build awareness of the critical risk factors on the execution of railway reconstruction project, measure the impact and occurrence likelihood for these risk factors. Subjectivity, uncertainty and vagueness within the assessment process are dealt with using linguistic variables parameterized by trapezoid fuzzy numbers. By multiplying the degree of impact and the occurrence likelihood of risk factors, estimated severity values of each identified risk factor are determined. Based on the assessment results, the construction agencies were informed of what risks should be noticed and what they should do to avoid the risks. That is, it enables construction agencies of railway reconstruction to plan the appropriate risk responses/strategies to increase the opportunity of project success and effectiveness. PMID:24772014

  11. Using fuzzy multiple criteria decision-making approach for assessing the risk of railway reconstruction project in Taiwan.

    Science.gov (United States)

    Lu, Shih-Tong; Yu, Shih-Heng; Chang, Dong-Shang

    2014-01-01

    This study investigates the risk factors in railway reconstruction project through complete literature reviews on construction project risks and scrutinizing experiences and challenges of railway reconstructions in Taiwan. Based on the identified risk factors, an assessing framework based on the fuzzy multicriteria decision-making (fuzzy MCDM) approach to help construction agencies build awareness of the critical risk factors on the execution of railway reconstruction project, measure the impact and occurrence likelihood for these risk factors. Subjectivity, uncertainty and vagueness within the assessment process are dealt with using linguistic variables parameterized by trapezoid fuzzy numbers. By multiplying the degree of impact and the occurrence likelihood of risk factors, estimated severity values of each identified risk factor are determined. Based on the assessment results, the construction agencies were informed of what risks should be noticed and what they should do to avoid the risks. That is, it enables construction agencies of railway reconstruction to plan the appropriate risk responses/strategies to increase the opportunity of project success and effectiveness.

  12. Sistem Pendukung Keputusan Untuk Pengadaan Fasilitas Hotel Menggunakan Metode TOPSIS

    OpenAIRE

    Susi Hendartie; Bayu Surarso; Beta Noranita

    2014-01-01

    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 ...

  13. Parallel Machine Scheduling Models with Fuzzy Parameters and Precedence Constraints: A Credibility Approach

    Institute of Scientific and Technical Information of China (English)

    HOU Fu-jun; WU Qi-zong

    2007-01-01

    A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided.For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers.Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated.Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints.The genetic algorithm is utilized to find the best solutions in a short period of time.An illustrative numerical example is also given.Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.

  14. Establishing the overall service quality of engineering education: fuzzy logic approach

    Science.gov (United States)

    Shekhar, N. Chandra; Venkatasubbaiah, K.; Kandukuria, N. R.

    2012-12-01

    Measuring overall service quality (OSQ) is gaining prominence in higher education due to the increased competition among engineering education institutions (EEIs) and growing awareness about value for money among the public. Determination of OSQ on certain institutional aspects is done by various agencies throughout the world. Each system uses a different set of weighted indicators to measure the overall service quality of institutions. Five service quality factors, namely professionalism, integrated education, facilities, responsiveness and empathy are considered in the study. Trapezoidal fuzzy numbers are used to determine the aggregate weights of the factors to handle the vagueness present in the linguistic values of the stakeholders' subjective opinions. Final weights of the factors are assessed by taking the distances of each factor between Fuzzy Positive Ideal Rating and Fuzzy Negative Ideal Rating. An illustrative study is presented to determine the OSQ of EEIs. The results help to focus on the factors which need immediate attention to enhance the quality of EEIs.

  15. Designing an organizational structure of administrative logistics using a fuzzy approach

    Directory of Open Access Journals (Sweden)

    Dragan S. Pamučar

    2012-07-01

    Full Text Available Various organizational structure options are proposed in the application of the given model, taking into account the fact that transport authorities should be designed and dimensioned so as to achieve the rudimentary goals and tasks for fulfillment of which they were established. Each task set before the transport authorities requires a reliable and top-quality performance in all environmental conditions. Since most of the acquired data is characterized by a high degree of imprecision, subjectivity and uncertainty, fuzzy logic was used for displaying these. Fuzzy linguistic descriptors were used for describing the criteria used for evaluating the proposed alternatives. In this way, fuzzy logic enables the exploitation of tolerance that exists in imprecision, uncertainty and partial truth of the acquired research results. The paper presents a model for designing the organizational structure of transport support authorities.

  16. On an Intuitionistic Fuzzy Approach for Decision Making in Medicine: Part 2

    Directory of Open Access Journals (Sweden)

    Peter Vassilev

    2007-10-01

    Full Text Available An idea presented in (6,7 has been developed further, and the patients readiness for weaning form long-term mechanical ventilation has been determined in the sense of intuitionistic fuzzy logic (1. In the present paper it is solved as pattern recognition problem. As a final estimate of the classification an estimate aggregated from four estimates, obtained by four different procedures: Stepwise discriminant analysis (SDA, stepwise logistic regression (SLR, "intuitionistic fuzzy" Voronoi diagrams (IFVD and nonpulmonary weaning index (NPWI, is taken. The aggregation of estimates is executed by the application of the second algorithm, proposed in (7. A comparison between the two algorithms has been made.

  17. 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.

  18. Assessment of BTEX-induced health risk under multiple uncertainties at a petroleum-contaminated site: An integrated fuzzy stochastic approach

    Science.gov (United States)

    Zhang, Xiaodong; Huang, Guo H.

    2011-12-01

    Groundwater pollution has gathered more and more attention in the past decades. Conducting an assessment of groundwater contamination risk is desired to provide sound bases for supporting risk-based management decisions. Therefore, the objective of this study is to develop an integrated fuzzy stochastic approach to evaluate risks of BTEX-contaminated groundwater under multiple uncertainties. It consists of an integrated interval fuzzy subsurface modeling system (IIFMS) and an integrated fuzzy second-order stochastic risk assessment (IFSOSRA) model. The IIFMS is developed based on factorial design, interval analysis, and fuzzy sets approach to predict contaminant concentrations under hybrid uncertainties. Two input parameters (longitudinal dispersivity and porosity) are considered to be uncertain with known fuzzy membership functions, and intrinsic permeability is considered to be an interval number with unknown distribution information. A factorial design is conducted to evaluate interactive effects of the three uncertain factors on the modeling outputs through the developed IIFMS. The IFSOSRA model can systematically quantify variability and uncertainty, as well as their hybrids, presented as fuzzy, stochastic and second-order stochastic parameters in health risk assessment. The developed approach haw been applied to the management of a real-world petroleum-contaminated site within a western Canada context. The results indicate that multiple uncertainties, under a combination of information with various data-quality levels, can be effectively addressed to provide supports in identifying proper remedial efforts. A unique contribution of this research is the development of an integrated fuzzy stochastic approach for handling various forms of uncertainties associated with simulation and risk assessment efforts.

  19. 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.

  20. Fuzzy Set Field and Fuzzy Metric

    OpenAIRE

    Gebru Gebray; B. Krishna Reddy

    2014-01-01

    The notation of fuzzy set field is introduced. A fuzzy metric is redefined on fuzzy set field and on arbitrary fuzzy set in a field. The metric redefined is between fuzzy points and constitutes both fuzziness and crisp property of vector. In addition, a fuzzy magnitude of a fuzzy point in a field is defined.