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Sample records for fuzzy mcdm approach

  1. Applying an integrated fuzzy gray MCDM approach: A case study on mineral processing plant site selection

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    Ezzeddin Bakhtavar

    2017-12-01

    Full Text Available The accurate selection of a processing plant site can result in decreasing total mining cost. This problem can be solved by multi-criteria decision-making (MCDM methods. This research introduces a new approach by integrating fuzzy AHP and gray MCDM methods to solve all decision-making problems. The approach is applied in the case of a copper mine area. The critical criteria are considered adjacency to the crusher, adjacency to tailing dam, adjacency to a power source, distance from blasting sources, the availability of sufficient land, and safety against floods. After studying the mine map, six feasible alternatives are prioritized using the integrated approach. Results indicated that sites A, B, and E take the first three ranks. The separate results of fuzzy AHP and gray MCDM confirm that alternatives A and B have the first two ranks. Moreover, the field investigations approved the results obtained by the approach.

  2. Combining Fuzzy MCDM with BSC Approach in Performance Evaluation of Iranian Private Banking Sector

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    Meysam Shaverdi

    2011-01-01

    Full Text Available The objective of this study is to construct an approach based on multiple criteria decision making (MCDM and balanced scorecard (BSC for evaluating performance for three nongovernmental Iranian's banks. Following the literature relating to banking performance and BSC concepts, experts and managers select 21 indexes for evaluation. Furthermore, fuzzy analytic hierarchy process (FAHP calculated the relative weights of each chosen index in order to tolerate vagueness and ambiguity of information, and three MCDM analytical tools (TOPSIS, VIKOR, and ELECTRE were adopted to rank the banking performance. The results indicate that a customer “” has the most significant BSC perspectives and the customer satisfaction “1” is the most major index in banking sector. This proposed fuzzy MCDM method combined with BSC approach is a comprehensive and up-to-date model that can be a useful and effective assessment tool.

  3. 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.

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

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    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.

  5. A fuzzy MCDM approach for evaluating school performance based on linguistic information

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    Musani, Suhaina; Jemain, Abdul Aziz

    2013-11-01

    Decision making is the process of finding the best option among the feasible alternatives. This process should consider a variety of criteria, but this study only focus on academic achievement. The data used is the percentage of candidates who obtained Malaysian Certificate of Education (SPM) in Melaka based on school academic achievement for each subject. 57 secondary schools in Melaka as listed by the Ministry of Education involved in this study. Therefore the school ranking can be done using MCDM (Multi Criteria Decision Making) methods. The objective of this study is to develop a rational method for evaluating school performance based on linguistic information. Since the information or level of academic achievement provided in linguistic manner, there is a possible chance of getting incomplete or uncertain problems. So in order to overcome the situation, the information could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this research, VIKOR (Multi Criteria Optimization and Compromise Solution) has been used as a MCDM tool for the school ranking process in fuzzy environment. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

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

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    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.

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

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    Tsung-Hsien Wu

    2017-11-01

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

  8. A MCDM Approach with Fuzzy AHP Method for Occupational Accidents on Board

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    ónal Özdemir

    2018-03-01

    Full Text Available Occupational accidents on board criteria determining is a challenging procedure in shipping industry as the ideal safety ship management strategy depends on many factors involving in shipping transportation There are many legislations, agreements and practices to obtain series of security measures in order to ensure safety and security of seafarers. Causes of on-board occupational accidents need to be evaluated in a correct manner to regulate more functional practices and also to lower the on-board accident rates. However, causes of on-board accidents can be extremely complex. Therefore, scientific methods should be used to evaluate the causes and to determine the measures to be taken. The evaluation of the parameters is of great importance for the future of the maritime sector and in terms of development. In this study, factors have been identified that lead to seafarers? occupational accidents on board and we tried to present alternative solutions which can be applied on this issue. Severity of the reasons that led to the accidents and their relationships with each other are identified to be able to sort through the alternative solutions with a model using the fuzzy AHP (Analytic Hierarchy Process method approach. Results of the study revealed that the most important criteria for the occupational accidents on board criteria selection are respectively; human factors, lack of management, ship-borne troubles, cargo troubles and environmental factors.

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

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    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

  10. Constructing Taipei City Sports Centre Performance Evaluation Model with Fuzzy MCDM Approach Based on Views of Managers

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    Chen-Yang Wang

    2013-01-01

    Full Text Available This study aims to utilize the fuzzy analytical/network process (FAHP/FANP and decision-making trial and evaluation laboratory (DEMATEL approach to recognize the influential indicators of sport centre business management in Taipei city’s sports centre. Twenty-three of sports centres with six-dimensions were identified from the literature review and interview with twelve experts (academic and practical experience. By considering the interrelationships among the indices, DEMATEL was used to deal with the importance and causal relationships among the evaluation indices of sports centre. Then, we employ the FAHP/FANP to determine the weight of each management criterion. Our empirical results provide two main insights: first, sports centre business management strategies comprise six-dimensions and 23 indexes; second, the FANP analysis shows that the six key factors are (in order of priority service price, site conditions, operations management, traffic conditions, sports products, and staff quality. This study uses the FANP and DEMATEL along with mathematical computing in order to provide sports centre managers with a reliable decision-making reference and to assist them in formulating the most effective business strategy possible.

  11. Stock selection using a hybrid MCDM approach

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    Tea Poklepović

    2014-12-01

    Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

  12. MENGUKUR KESUKSESAN PRODUK PADA TAHAP DESAIN: SEBUAH PENDEKATAN FUZZY-MCDM

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    Ade Febransyah

    2006-01-01

    Full Text Available It has always been a great challenge to any product development team to forecast the success of a new product at the design stage. For any product concept, it is of interest to assign an accurate probability to any event or state of the world that reflects the new product success. This probability is then required in decision tree analysis for selecting the best product concept. In practice, the probability is determined solely on intuition or subjective judgment due to impreciseness, lack of information during the design stage, and the cognitive limitation of decision makers. This paper presents an approach integrating fuzzy set theory and multi criteria decision making (MCDM approach in forecasting accurately the success of a new product. The analytic hierarchy process (AHP is used due to its simplicity as a prescriptive approach that will help decision makers select the best decision with respect to a set of criteria. Fuzzy numbers are used to describe any judgment on design criteria and the event probability of a product concept. A numerical example is given to illustrate the use of this approach. Abstract in Bahasa Indonesia : Selalu menjadi tantangan besar bagi setiap tim pengembang produk untuk dapat mengestimasi tingkat kesuksesan suatu produk baru pada tahap desain. Tingkat kesuksesan yang dinyatakan dengan besar probabilitas berbagai state of the world dari suatu konsep produk selanjutnya digunakan dalam analisa keputusan untuk memilih konsep produk terlayak. Selama ini besar probabilitas ditentukan lebih banyak berdasarkan intuisi dan subyektifitas pengambil keputusan. Praktik ini cenderung menghasilkan keputusan yang bias mengingat keterbatasan kapabilitas kognitif manusia dalam mensintesa berbagai keunggulan maupun kekurangan dari sekumpulan konsep produk. Tulisan ini bertujuan untuk menyampaikan satu pendekatan yang mengintegrasikan logika fuzzy dan pendekatan pengambilan keputusan berkriteria jamak (multi criteria decision making

  13. The Fuzzy MCDM Algorithms for the M&A Due Diligence

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    Chung-Tsen Tsao

    2008-04-01

    Full Text Available An M&A due diligence is the process in which one of the parties to the transaction undertakes to investigate the other in order to judge whether to go forward with the transaction on the terms proposed. It encompasses the missions in three phases: searching and preliminary screening potential candidates, evaluating the candidates and deciding the target, and assisting the after-transaction integration. This work suggests using a Fuzzy Multiple Criteria Decision Making approach (Fuzzy MCDM and develops detailed algorithms to carry out the second-phase task. The approach of MCDM is able to facilitate the analysis and integration of information from different aspects and criteria. The theory of Fuzzy Sets can include qualitative information in addition to quantitative information. In the developed algorithms the evaluators' subjective judgments are expressed in linguistic terms which can better reflect human intuitive thought than the quantitative scores. These linguistic judgments are transformed into fuzzy numbers and made subsequent synthesis with quantitative financial figures. The order of candidates can be ranked after a defuzzification. Then the acquiring firm can work out a more specific study, including pricing and costing, on the priority candidates so as to decide the target.

  14. An integrated MCDM approach to green supplier selection

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    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.

  15. Technology Evaluation and Selection of 3DIC Integration Using a Three-Stage Fuzzy MCDM

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    Yen-Chun Lee

    2016-01-01

    Full Text Available For the purpose of the sustainable development in the global semiconductor industry, emerging three-dimensional integrated circuit (3DIC integration technologies have demonstrated their importance as potential candidates for extending the lifespan of Moore’s Law. This study aimed to explore a technology selection process involving a three-stage fuzzy multicriteria decision-making (MCDM approach to facilitate the effective assessment of emerging 3DIC integration technologies. The fuzzy Delphi method was first used to determine the important criteria. The fuzzy analytic hierarchy process (fuzzy AHP was then adopted to derive the weights of the criteria. The fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS was finally deployed to rate the alternatives. Empirical results indicate that market potential, time-to-market, and heterogeneous integration are the top three decision criteria for the selection of 3DIC integration technologies. Furthermore, 2.5D through-silicon interposer (TSI is of primary interest to the Taiwanese semiconductor industry, followed by 3DIC through-silicon via (TSV, 3D packaging, and 3D silicon TSV (Si TSV. The proposed three-stage fuzzy decision model may potentially assist industry practitioners and government policy-makers in directing research and development investments and allocating resources more strategically.

  16. Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research

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    Antucheviciene, Jurgita; Kala, Zdeněk; Marzouk, Mohamed; Egidijus R. Vaidogas

    2015-01-01

    The present review examines decision-making methods developed for dealing with uncertainties and applied to solve problems of civil engineering. Several methodological difficulties emerging from uncertainty quantification in decision-making are identified. The review is focused on formal methods of multiple criteria decision-making (MCDM). Handling of uncertainty by means of fuzzy logic and probabilistic modelling is analysed in light of MCDM. A sensitivity analysis of MCDM problems with unce...

  17. A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

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    Dursun, Mehtap

    2017-06-01

    Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

  18. Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research

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    Jurgita Antucheviciene

    2015-01-01

    Full Text Available The present review examines decision-making methods developed for dealing with uncertainties and applied to solve problems of civil engineering. Several methodological difficulties emerging from uncertainty quantification in decision-making are identified. The review is focused on formal methods of multiple criteria decision-making (MCDM. Handling of uncertainty by means of fuzzy logic and probabilistic modelling is analysed in light of MCDM. A sensitivity analysis of MCDM problems with uncertainties is discussed. An application of stochastic MCDM methods to a design of safety critical objects of civil engineering is considered. Prospects of using MCDM under uncertainty in developing areas of civil engineering are discussed in brief. These areas are design of sustainable and energy efficient buildings, building information modelling, and assurance of security and safety of built property. It is stated that before long the decision-making in civil engineering may face several methodological problems: the need to combine fuzzy and probabilistic representations of uncertainties in one decision-making matrix, the necessity to extend a global sensitivity analysis to all input elements of a MCDM problem with uncertainties, and an application of MCDM methods in the areas of civil engineering where decision-making under uncertainty is presently not common.

  19. Green material selection for sustainability: A hybrid MCDM approach.

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    Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng

    2017-01-01

    Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection.

  20. FMEA using uncertainty theories and MCDM methods

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    Liu, Hu-Chen

    2016-01-01

    This book offers a thorough and systematic introduction to the modified failure mode and effect analysis (FMEA) models based on uncertainty theories (e.g. fuzzy logic, intuitionistic fuzzy sets, D numbers and 2-tuple linguistic variables) and various multi-criteria decision making (MCDM) approaches such as distance-based MCDM, compromise ranking MCDM and hybrid MCDM, etc. As such, it provides essential FMEA methods and practical examples that can be considered in applying FMEA to enhance the reliability and safety of products and services. The book offers a valuable guide for practitioners and researchers working in the fields of quality management, decision making, information science, management science, engineering, etc. It can also be used as a textbook for postgraduate and senior undergraduate students.

  1. An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness.

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    Nguyen, Huu-Tho; Dawal, Siti Zawiah Md; Nukman, Yusoff; Rifai, Achmad P; Aoyama, Hideki

    2016-01-01

    The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts' uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

  2. A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries

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    Zoraghi, Nima; Amiri, Maghsoud; Talebi, Golnaz; Zowghi, Mahdi

    2013-12-01

    This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.

  3. Evaluation of performance metrics of leagile supply chain through fuzzy MCDM

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    D. Venkata Ramana

    2013-07-01

    Full Text Available Leagile supply chain management has emerged as a proactive approach for improving business value of companies. The companies that face volatile and unpredictable market demand of their products must pioneer in leagile supply chain strategy for competition and various demands of customers. There are literally many approaches for performance metrics of supply chain in general, yet little investigation has identified the reliability and validity of such approaches particularly in leagile supply chains. This study examines the consistency approaches by confirmatory factor analysis that determines the adoption of performance dimensions. The prioritization of performance enablers under these dimensions of leagile supply chain in small and medium enterprises are determined through fuzzy logarithmic least square method (LLSM. The study developed a generic hierarchy model for decision-makers who can prioritize the supply chain metrics under performance dimensions of leagile supply chain.

  4. A fuzzy AHP approach for employee recruitment

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    Mohsen Varmazyar; Behrouz Nouri

    2014-01-01

    Human resource management plays an essential role on development of any business organization. Selection of employee normally depends on various criteria such as employee commitment, necessary skills, etc. Therefore, a good strategy to hire appropriate employee is a multi-criteria decision making (MCDM) specially the ones, which could handle uncertainty, properly. In this paper, we present a method to use MCDM techniques for hiring employees. In fact, the present work proposes a Fuzzy Analyti...

  5. Modelling a suitable location for Urban Solid Waste Management using AHP method and GIS -A geospatial approach and MCDM Model

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    Iqbal, M.; Islam, A.; Hossain, A.; Mustaque, S.

    2016-12-01

    Multi-Criteria Decision Making(MCDM) is advanced analytical method to evaluate appropriate result or decision from multiple criterion environment. Present time in advanced research, MCDM technique is progressive analytical process to evaluate a logical decision from various conflict. In addition, Present day Geospatial approach (e.g. Remote sensing and GIS) also another advanced technical approach in a research to collect, process and analyze various spatial data at a time. GIS and Remote sensing together with the MCDM technique could be the best platform to solve a complex decision making process. These two latest process combined very effectively used in site selection for solid waste management in urban policy. The most popular MCDM technique is Weighted Linear Method (WLC) where Analytical Hierarchy Process (AHP) is another popular and consistent techniques used in worldwide as dependable decision making. Consequently, the main objective of this study is improving a AHP model as MCDM technique with Geographic Information System (GIS) to select a suitable landfill site for urban solid waste management. Here AHP technique used as a MCDM tool to select the best suitable landfill location for urban solid waste management. To protect the urban environment in a sustainable way municipal waste needs an appropriate landfill site considering environmental, geological, social and technical aspect of the region. A MCDM model generate from five class related which related to environmental, geological, social and technical using AHP method and input the result set in GIS for final model location for urban solid waste management. The final suitable location comes out that 12.2% of the area corresponds to 22.89 km2 considering the total study area. In this study, Keraniganj sub-district of Dhaka district in Bangladesh is consider as study area which is densely populated city currently undergoes an unmanaged waste management system especially the suitable landfill sites for

  6. Analyzing the drivers of green manufacturing with fuzzy approach

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

    2015-01-01

    Green issues have gained more importance in contemporary globalization. Recent years have seen manufacturing processes understand the green issues due to the social and environmental concerns involved. The drivers of green manufacturing, however, have not been thoroughly investigated. Thus...... India, and aided by their replies; a pair-wise comparison was made among the drivers. The pair-wise comparison is used as an input data and the drivers were analyzed on its basis. The analysis resorted to the use of a fuzzy Multi Criteria Decision Making (MCDM) approach. The obtained results...

  7. Fuzzy axiomatic design approach based green supplier selection

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    Kannan, Devika; Govindan, Kannan; Rajendran, Sivakumar

    2015-01-01

    proposes a multi-criteria decision-making (MCDM) approach called Fuzzy Axiomatic Design (FAD) to select the best green supplier for Singapore-based plastic manufacturing company. At first, the environmental criteria was developed along with the traditional criteria based on the literature review...... and company requirements. Next, the FAD methodology evaluates the requirements of both the manufacturer (design needs) and the supplier (functional needs), and because multiple criteria must be considered, a multi-objective optimization model of a fuzzy nature must be developed. The application...... of the proposed approach in the case company has been illustrated and the result of this study helps firm to establish the systematic approach to select the best green supplier within the set of criteria. When the proposed methodology is applied, it allows not only to select the most appropriate green supplier...

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

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    Leili Afkham

    2012-01-01

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

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

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    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.

  10. 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.

  11. Application of fuzzy goal programming approach to multi-objective linear fractional inventory model

    Science.gov (United States)

    Dutta, D.; Kumar, Pavan

    2015-09-01

    In this paper, we propose a model and solution approach for a multi-item inventory problem without shortages. The proposed model is formulated as a fractional multi-objective optimisation problem along with three constraints: budget constraint, space constraint and budgetary constraint on ordering cost of each item. The proposed inventory model becomes a multiple criteria decision-making (MCDM) problem in fuzzy environment. This model is solved by multi-objective fuzzy goal programming (MOFGP) approach. A numerical example is given to illustrate the proposed model.

  12. Multicriteria decision-making approach with hesitant interval-valued intuitionistic fuzzy sets.

    Science.gov (United States)

    Peng, Juan-juan; Wang, Jian-qiang; Wang, Jing; Chen, Xiao-hong

    2014-01-01

    The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based on t-conorms and t-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einstein t-conorms and t-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis.

  13. A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

    Directory of Open Access Journals (Sweden)

    Animesh Debnath

    2017-07-01

    Full Text Available Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS. The initial adaptation of strategic portfolio management of genetically modified (GM Agro by-products (Ab-Ps is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL, Multi-Attributive Border Approximation area Comparison (MABAC and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs. The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR and agro export promotion.

  14. A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach.

    Science.gov (United States)

    Varmazyar, Mohsen; Dehghanbaghi, Maryam; Afkhami, Mehdi

    2016-10-01

    Balanced Scorecard (BSC) is a strategic evaluation tool using both financial and non-financial indicators to determine the business performance of organizations or companies. In this paper, a new integrated approach based on the Balanced Scorecard (BSC) and multi-criteria decision making (MCDM) methods are proposed to evaluate the performance of research centers of research and technology organization (RTO) in Iran. Decision-Making Trial and Evaluation Laboratory (DEMATEL) are employed to reflect the interdependencies among BSC perspectives. Then, Analytic Network Process (ANP) is utilized to weight the indices influencing the considered problem. In the next step, we apply four MCDM methods including Additive Ratio Assessment (ARAS), Complex Proportional Assessment (COPRAS), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking of alternatives. Finally, the utility interval technique is applied to combine the ranking results of MCDM methods. Weighted utility intervals are computed by constructing a correlation matrix between the ranking methods. A real case is presented to show the efficacy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. A fuzzy AHP approach for employee recruitment

    Directory of Open Access Journals (Sweden)

    Mohsen Varmazyar

    2014-01-01

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

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

    Science.gov (United States)

    Chung, Eun-Sung; Kim, Yeonjoo

    2014-12-15

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

  17. 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.

  18. The Evaluation of Mineral Resources Development Efficiency Based on Hesitant Fuzzy Linguistic Approach and Modified TODIM

    Directory of Open Access Journals (Sweden)

    Pu Li

    2018-01-01

    Full Text Available The evaluation of mineral resources development efficiency is a typical multicriteria decision-making issue. Meanwhile, due to the limited existing technology, there might be subjectivity, ambiguity, and inaccuracy of the measurement of the evaluation index of mineral resources development efficiency. In this paper, we, considering the incomplete information, use the hesitant fuzzy linguistic approach to describe the psychological hesitation and ambiguity of the decision-maker in the actual evaluation process and then construct the general model of the development efficiency evaluation of the mineral resources by using the hesitant fuzzy linguistic terms sets and modified TODIM. Finally, this paper takes the Panxi area as an example to study the development efficiency of vanadium-titanium magnetite. The results show that the hesitant fuzzy linguistic multicriteria decision-making (MCDM approach can be implemented to mineral resources evaluation and resources management.

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

    International Nuclear Information System (INIS)

    Onuet, Semih; Soner, Selin

    2008-01-01

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

  20. 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

  1. 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.

  2. 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.

  3. A New Approach to Fuzzy Arithmetic

    OpenAIRE

    Popov, Antony

    2010-01-01

    This work shows an application of a generalized approach for constructing dilation-erosion adjunctions on fuzzy sets. More precisely, operations on fuzzy quantities and fuzzy numbers are considered. By the generalized approach an analogy with the well known interval computations could be drawn and thus we can define outer and inner operations on fuzzy objects. These operations are found to be useful in the control of bioprocesses, ecology and other domains where data uncerta...

  4. 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.

  5. 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....

  6. National Options for a Sustainable Nuclear Energy System: MCDM Evaluation Using an Improved Integrated Weighting Approach

    Directory of Open Access Journals (Sweden)

    Ruxing Gao

    2017-12-01

    Full Text Available While the prospects look bright for nuclear energy development in China, no consensus about an optimum transitional path towards sustainability of the nuclear fuel cycle has been achieved. Herein, we present a preliminary study of decision making for China’s future nuclear energy systems, combined with a dynamic analysis model. In terms of sustainability assessment based on environmental, economic, and social considerations, we compared and ranked the four candidate options of nuclear fuel cycles combined with an integrated evaluation analysis using the Multi-Criteria Decision Making (MCDM method. An improved integrated weighting method was first applied in the nuclear fuel cycle evaluation study. This method synthesizes diverse subjective/objective weighting methods to evaluate conflicting criteria among the competing decision makers at different levels of expertise and experience. The results suggest that the fuel cycle option of direct recycling of spent fuel through fast reactors is the most competitive candidate, while the fuel cycle option of direct disposal of all spent fuel without recycling is the least attractive for China, from a sustainability perspective. In summary, this study provided a well-informed decision-making tool to support the development of national nuclear energy strategies.

  7. An Evaluation Model of Quantitative and Qualitative Fuzzy Multi-Criteria Decision-Making Approach for Location Selection of Transshipment Ports

    Directory of Open Access Journals (Sweden)

    Ji-Feng Ding

    2013-01-01

    Full Text Available The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study.

  8. Garage Location Selection for Public Transportation System in Istanbul: An Integrated Fuzzy AHP and Fuzzy Axiomatic Design Based Approach

    Directory of Open Access Journals (Sweden)

    Özge Nalan Bilişik

    2014-01-01

    Full Text Available We try to determine the best location for a bus garage, in which maintenance and repair activities are operated, for public transportation system in Istanbul. An integrated multicriteria decision making technique (MCDM is used to obtain reliable results. Firstly, various criteria related to garage location selection are specified and weighted by fuzzy AHP (analytical hierarchy process. Then, these weights are used in fuzzy axiomatic design (AD technique to determine the precedencies of the alternative garage locations.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Automatic approach to deriving fuzzy slope positions

    Science.gov (United States)

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

    2018-03-01

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

  11. Generalized Single-Valued Neutrosophic Hesitant Fuzzy Prioritized Aggregation Operators and Their Applications to Multiple Criteria Decision-Making

    Directory of Open Access Journals (Sweden)

    Rui Wang

    2018-01-01

    Full Text Available Single-valued neutrosophic hesitant fuzzy set (SVNHFS is a combination of single-valued neutrosophic set and hesitant fuzzy set, and its aggregation tools play an important role in the multiple criteria decision-making (MCDM process. This paper investigates the MCDM problems in which the criteria under SVNHF environment are in different priority levels. First, the generalized single-valued neutrosophic hesitant fuzzy prioritized weighted average operator and generalized single-valued neutrosophic hesitant fuzzy prioritized weighted geometric operator are developed based on the prioritized average operator. Second, some desirable properties and special cases of the proposed operators are discussed in detail. Third, an approach combined with the proposed operators and the score function of single-valued neutrosophic hesitant fuzzy element is constructed to solve MCDM problems. Finally, an example of investment selection is provided to illustrate the validity and rationality of the proposed method.

  12. The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making

    Science.gov (United States)

    Peng, Juan-juan; Wang, Jian-qiang; Wu, Xiao-hui; Zhang, Hong-yu; Chen, Xiao-hong

    2015-10-01

    In this paper, the cross-entropy of intuitionistic hesitant fuzzy sets (IHFSs) is developed by integrating the cross-entropy of intuitionistic fuzzy sets (IFSs) and hesitant fuzzy sets (HFSs). First, several measurement formulae are discussed and their properties are studied. Then, two approaches, which are based on the developed intuitionistic hesitant fuzzy cross-entropy, are proposed for solving multi-criteria decision-making (MCDM) problems within an intuitionistic hesitant fuzzy environment. For both methods, an optimisation model is established in order to determine the weight vector for MCDM problems with incomplete information on criteria weights. Finally, an example is provided in order to illustrate the practicality and effectiveness of the proposed approaches.

  13. 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.

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

    OpenAIRE

    Dhruba Das; Hemanta K. Baruah

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2018-01-01

    , and provide solutions for accountability, control and monitor the risks in the economic and production cycle. This study aims to develop a framework for the sustainable supply chain risk management (SSCRM) evaluation. To this end, an integrated fuzzy multi-criteria decision-making (MCDM) approach is proposed...... criteria and forty-four sub-criteria were developed for the final evaluation SSCRM framework. The most dominant sub-criteria in each group found to be as; machines & equipment risks, key supplier failures, demand fluctuations, government policy risks, IT security, economic issues, and lack of proper sewage......Supply chain risk management research has mainly mistreated the important of sustainability issues. Moreover, there is little knowledge about sustainable management of risk and supply chain and the way they impose losses for firms. Risk management's duty in the supply chain is to identify, analyze...

  16. 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.

  17. A Combined Fuzzy-AHP and Fuzzy-GRA Methodology for Hydrogen Energy Storage Method Selection in Turkey

    Directory of Open Access Journals (Sweden)

    Aytac Yildiz

    2013-06-01

    Full Text Available In this paper, we aim to select the most appropriate Hydrogen Energy Storage (HES method for Turkey from among the alternatives of tank, metal hydride and chemical storage, which are determined based on expert opinions and literature review. Thus, we propose a Buckley extension based fuzzy Analytical Hierarchical Process (Fuzzy-AHP and linear normalization based fuzzy Grey Relational Analysis (Fuzzy-GRA combined Multi Criteria Decision Making (MCDM methodology. This combined approach can be applied to a complex decision process, which often makes sense with subjective data or vague information; and used to solve to solve HES selection problem with different defuzzification methods. The proposed approach is unique both in the HES literature and the MCDM literature.

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

    Directory of Open Access Journals (Sweden)

    Mahdi Karbasian1

    2012-02-01

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

  20. 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.

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

    Indian Academy of Sciences (India)

    ALI EBRAHIMNEJAD

    fuzzy modified distribution method to obtain the optimal solution in terms of fuzzy numbers. Pandian & Natarajan. [13] introduced a new algorithm namely, fuzzy zero point method for finding fuzzy optimal solution for such FTP in which the transportation cost, supply and demand are represented by trapezoidal fuzzy numbers.

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

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

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

  3. 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.

  4. Postmodern Fuzzy System Theory: A Deconstruction Approach Based on Kabbalah

    Directory of Open Access Journals (Sweden)

    Gabriel Burstein

    2014-11-01

    Full Text Available Modern general system theory proposed a holistic integrative approach based on input-state-output dynamics as opposed to the traditional reductionist detail based approach. Information complexity and uncertainty required a fuzzy system theory, based on fuzzy sets and fuzzy logic. While successful in dealing with analysis, synthesis and control of technical engineering systems, general system theory and fuzzy system theory could not fully deal with humanistic and human-like intelligent systems which combine technical engineering components with human or human-like components characterized by their cognitive, emotional/motivational and behavioral/action levels of operation. Such humanistic systems are essential in artificial intelligence, cognitive and behavioral science applications, organization management and social systems, man-machine systems or human factor systems, behavioral knowledge based economics and finance applications. We are introducing here a “postmodern fuzzy system theory” for controlled state dynamics and output fuzzy systems and fuzzy rule based systems using our earlier postmodern fuzzy set theory and a Kabbalah possible worlds model of modal logic and semantics type. In order to create a postmodern fuzzy system theory, we “deconstruct” a fuzzy system in order to incorporate in it the cognitive, emotional and behavioral actions and expressions levels characteristic for humanistic systems. Kabbalah offers a structural, fractal and hierarchic model for integrating cognition, emotions and behavior. We obtain a canonic deconstruction for a fuzzy system into its cognitive, emotional and behavioral fuzzy subsystems.

  5. ELV Recycling Service Provider Selection Using the Hybrid MCDM Method: A Case Application in China

    Directory of Open Access Journals (Sweden)

    Fuli Zhou

    2016-05-01

    Full Text Available With the rapid depletion of natural resources and undesired environmental changes globally, more interest has been shown in the research of green supply chain practices, including end-of-life vehicle (ELV recycling. The ELV recycling is mandatory for auto-manufacturers by legislation for the purpose of minimizing potential environmental damages. The purpose of the present research is to determine the best choice of ELV recycling service provider by employing an integrating hybrid multi-criteria decision making (MCDM method. In this research, economic, environmental and social factors are taken into consideration. The linguistic variables and trapezoidal fuzzy numbers (TFNs are applied into this evaluation to deal with the vague and qualitative information. With the combined weight calculation of criteria based on fuzzy aggregation and Shannon Entropy techniques, the normative multi-criteria optimization technique (FVIKOR method is applied to explore the best solution. An application was performed based on the proposed hybrid MCDM method, and sensitivity analysis was conducted on different decision making scenarios. The present study provides a decision-making approach on ELV recycling business selection under sustainability and green philosophy with high robustness and easy implementation.

  6. Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers

    Science.gov (United States)

    Ridzuan, Siti Amnah Mohd; Mohamad, Daud; Kamis, Nor Hanimah

    2014-12-01

    Multi-Criteria Decision Making (MCDM) methods have been developed to help decision makers in selecting the best criteria or alternatives from the options given. One of the well known methods in MCDM is the Consistent Fuzzy Preference Relation (CFPR) method, essentially utilizes a pairwise comparison approach. This method was later improved to cater subjectivity in the data by using fuzzy set, known as the Consistent Linguistic Fuzzy Preference Relations (CLFPR). The CLFPR method uses the additive transitivity property in the evaluation of pairwise comparison matrices. However, the calculation involved is lengthy and cumbersome. To overcome this problem, a method of defuzzification was introduced by researchers. Nevertheless, the defuzzification process has a major setback where some information may lose due to the simplification process. In this paper, we propose a method of CLFPR that preserves the fuzzy numbers form throughout the process. In obtaining the desired ordering result, a method of ranking fuzzy numbers is utilized in the procedure. This improved procedure for CLFPR is implemented to a case study to verify its effectiveness. This method is useful for solving decision making problems and can be applied to many areas of applications.

  7. Fuzzy outranking approach: A knowledge-driven method for mineral prospectivity mapping

    Science.gov (United States)

    Abedi, Maysam; Norouzi, Gholam-Hossain; Fathianpour, Nader

    2013-04-01

    This paper describes the application of a new multi-criteria decision making (MCDM) technique called fuzzy outranking to map prospectivity for porphyry Cusbnd Mo deposits. Various raster-based evidential layers involving geological, geophysical, and geochemical geo-data sets are integrated for mineral prospectivity mapping (MPM). In a case study, 13 layers of the Now Chun deposit located in the Kerman province of Iran are used to explore the region of interest. The outputs are validated using 21 boreholes drilled in this area. Comparison of the output prospectivity map with concentrations of Cu and Mo in the boreholes indicates that the fuzzy outranking MCDM is a useful tool for MPM. The proposed method shows a high performance for MPM thereby reducing the cost of exploratory drilling in the study area.

  8. Fuzzy Multi-criteria Decision Making Associated with Risk and Confidence Attributes

    OpenAIRE

    Meshram, Chandrashekhar; Agrawal, Shyam Sundar

    2015-01-01

    The multicriteria decision problems involve uncertainty, it is important to incorporate different types of uncertainty in any proposed solution. In this paper, we presented fuzzy MCDM approach based on risk and confidence analysis that we believe is effective in tackling complex, ill-defined and human-oriented decision problems.

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

    African Journals Online (AJOL)

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

  10. 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.

  11. 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

  12. 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;

  13. A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

  14. A comparative approach for ranking contaminated sites based on the risk assessment paradigm using fuzzy PROMETHEE.

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

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

    Directory of Open Access Journals (Sweden)

    H. Handan DEMIR

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Aydin Torkabadi

    2018-03-01

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

  17. Hesitant fuzzy linguistic multicriteria decision-making method based on generalized prioritized aggregation operator.

    Science.gov (United States)

    Wu, Jia-ting; Wang, Jian-qiang; Wang, Jing; Zhang, Hong-yu; Chen, Xiao-hong

    2014-01-01

    Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

  18. 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.

  19. Permutation based decision making under fuzzy environment using Tabu search

    Directory of Open Access Journals (Sweden)

    Mahdi Bashiri

    2012-04-01

    Full Text Available One of the techniques, which are used for Multiple Criteria Decision Making (MCDM is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method.

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

    Directory of Open Access Journals (Sweden)

    Marija Zahar Djordjevic

    2014-06-01

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

  1. 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.

  2. 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....

  3. 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

  4. Improvements to Earthquake Location with a Fuzzy Logic Approach

    Science.gov (United States)

    Gökalp, Hüseyin

    2018-01-01

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

  5. A logical approach to fuzzy truth hedges

    Czech Academy of Sciences Publication Activity Database

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

    2013-01-01

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

  6. Empirical Bayes Approaches to Multivariate Fuzzy Partitions.

    Science.gov (United States)

    Woodbury, Max A.; Manton, Kenneth G.

    1991-01-01

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

  7. 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.

  8. Modeling Academic Performance Evaluation Using Soft Computing Techniques: A Fuzzy Logic Approach

    OpenAIRE

    Ramjeet Singh Yadav; Vijendra Pratap Singh

    2011-01-01

    We have proposed a Fuzzy Expert System (FES) for student academic performance evaluation based on fuzzy logic techniques. A suitable fuzzy inference mechanism and associated rule has been discussed. It introduces the principles behind fuzzy logic and illustrates how these principles could be applied by educators to evaluating student academic performance. Several approaches using fuzzy logic techniques have been proposed to provide a practical method for evaluating student academic performanc...

  9. A fuzzy approach for modelling radionuclide in lake system

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  10. 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.

  11. A state-of-art survey on TQM applications using MCDM techniques

    Directory of Open Access Journals (Sweden)

    Yasaman Mohammadshahi

    2013-07-01

    Full Text Available In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1 AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2 DEMATEL and Fuzzy DEMATEL, (3 GRA, (4 Vikor and Fuzzy Vikor, (5 TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6 Fuzzy and (7 Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches.

  12. 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

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

    Indian Academy of Sciences (India)

    SANKAR KUMAR ROY

    2018-02-07

    Feb 7, 2018 ... Keywords. Transportation problem; multi-objective decision making; intuitionistic fuzzy programming; interval programming; goal ... approach to solve the MOTP with nonlinear cost and multi- choice demand. Rani and .... division and scalar multiplication of interval numbers are described as follows: Addition ...

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2013-10-01

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

  17. A new approach for automatic control modeling, analysis and design in fully fuzzy environment

    OpenAIRE

    Gabr, Walaa Ibrahim

    2015-01-01

    The paper presents a new approach for the modeling, analysis and design of automatic control systems in fully fuzzy environment based on the normalized fuzzy matrices. The approach is also suitable for determining the propagation of fuzziness in automatic control and dynamical systems where all system coefficients are expressed as fuzzy parameters. A new consolidity chart is suggested based on the recently newly developed system consolidity index for testing the susceptibility of the system t...

  18. A Comparative Study on Sugeno Integral Approach to Aggregation of Experts' Opinion

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Seong Ho; Kim, Kil Yoo; Kim, Tae Woon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2007-07-01

    A multicriteria decision-making (MCDM) problem of preference ranking of various alternatives is common in science and engineering fields. Usually, the MCDM problem is characterized in terms of two factors: relative importance of each evaluation criterion and appropriateness of each alternative. The ranking is determined by a relative degree of appropriateness of decision alternatives. In reality, there are different grades of interaction among decision criteria. One of well-known approaches to aggregation of those two factors is the weighted arithmetic mean (WAM) approach. Here, importance weights for criteria are viewed as probability measures. The weights are linearly aggregated with appropriateness values. In the present work, the main objective is to study an aggregation model with various grades of interactions among the decision elements. The successful applications of fuzzy integral aggregation operators to subjective MCDM problems have been motivating this work. On the basis of {lambda}-fuzzy measures and Sugeno integral (SI), the SI aggregation approach is proposed. Here, interaction among criteria is dealt with {lambda}-fuzzy measures. Aggregation of these measures and appropriateness values is implemented, especially, by the Sugeno integral as one of fuzzy integrals. Aggregated values obtained by the SI approach are viewed as decision maker's pessimistic (or conservative) attitude towards information aggregation, compared to the WAM approach. Firstly, the concepts of the {lambda}-fuzzy measure and the Sugeno fuzzy integral are introduced. Then, as an application of the SI approach, an illustrative example is given.

  19. Hesitant Trapezoidal Fuzzy QUALIFLEX Method and Its Application in the Evaluation of Green Supply Chain Initiatives

    Directory of Open Access Journals (Sweden)

    Xiaolu Zhang

    2016-09-01

    Full Text Available This paper explores how to handle multiple criteria decision-making (MCDM problems in which the criteria values of alternatives take the form of comparative linguistic expressions. Firstly, the new concept of hesitant trapezoidal fuzzy numbers (HTrFNs is provided to model the semantics of the comparative linguistic expressions. Then, the operational laws and the distance measures of HTrFNs are presented. Afterwards, a useful outranking method, the hesitant trapezoidal fuzzy QUALIFLEX method, is developed to handle the MCDM problems with hierarchical structure in the environment of HTrFN. At length, the proposed method is applied to evaluating green supply chain initiatives in order to achieve sustainable economic and environmental performance, and a case study concerned with a fashion retail chain is presented to demonstrate its feasibility and applicability, also, a comparative analysis with other relevant approaches is conducted to validate the effectiveness of the proposed method.

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

    Science.gov (United States)

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

    2007-10-01

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

  1. INFORMATION SYSTEMS OUTSOURCING DECISIONS UNDER FUZZY GROUP DECISION MAKING APPROACH

    OpenAIRE

    S. NAZARI-SHIRKOUHI; A. ANSARINEJAD; SS. MIRI-NARGESI; V. MAJAZI DALFARD; K. REZAIE

    2011-01-01

    During the last decade, information system (IS) outsourcing has emerged as a major issue for organizations. As outsourcing decisions are often based on multicriteria approaches and group decisions, this paper proposes a structured methodology based on Fuzzy group decision making approach to evaluate and select the appropriate information system project (ISP) in an actual case. To achieve our purpose, we argue that seven criteria consisting of risk, management, economics, technology, resource,...

  2. Bimodal Fuzzy Analytic Hierarchy Process (BFAHP) For Coronary Heart Disease Risk Assessment.

    Science.gov (United States)

    Sabahi, Farnaz

    2018-04-03

    Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors. Copyright © 2018 Elsevier Inc. All

  3. Ranking Schools' Academic Performance Using a Fuzzy VIKOR

    Science.gov (United States)

    Musani, Suhaina; Aziz Jemain, Abdul

    2015-06-01

    Determination rank is structuring alternatives in order of priority. It is based on the criteria determined for each alternative involved. Evaluation criteria are performed and then a composite index composed of each alternative for the purpose of arranging in order of preference alternatives. This practice is known as multiple criteria decision making (MCDM). There are several common approaches to MCDM, one of the practice is known as VIKOR (Multi-criteria Optimization and Compromise Solution). The objective of this study is to develop a rational method for school ranking based on linguistic information of a criterion. The school represents an alternative, while the results for a number of subjects as the criterion. The results of the examination for a course, is given according to the student percentage of each grade. Five grades of excellence, honours, average, pass and fail is used to indicate a level of achievement in linguistics. Linguistic variables are transformed to fuzzy numbers to form a composite index of school performance. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

  4. Fuzzy neural approach for colon cancer prediction | Obi | Scientia ...

    African Journals Online (AJOL)

    fuzzy inference procedure. The proposed system which is self-learning and adaptive is able to handle the uncertainties often associated with the diagnosis and analysis of colon cancer. Keywords: Neural Network, Fuzzy logic, Neuro Fuzzy System, ...

  5. 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

  6. 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.

  7. 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 ...

  8. Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

    Science.gov (United States)

    Mohd, Wan Rosanisah Wan; Abdullah, Lazim

    2017-11-01

    A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.

  9. A NEW APPROACH ON SHORTEST PATH IN FUZZY ENVIRONMENT

    OpenAIRE

    A. Nagoorgani; A. Mumtaj Begam

    2010-01-01

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

  10. An approach to explainable deep learning using fuzzy inference

    Science.gov (United States)

    Bonanno, David; Nock, Kristen; Smith, Leslie; Elmore, Paul; Petry, Fred

    2017-05-01

    Deep Learning has proven to be an effective method for making highly accurate predictions from complex data sources. Convolutional neural networks continue to dominate image classification problems and recursive neural networks have proven their utility in caption generation and language translations. While these approaches are powerful, they do not offer explanation for how the output is generated. Without understanding how deep learning arrives at a solution there is no guarantee that these networks will transition from controlled laboratory environments to fieldable systems. This paper presents an approach for incorporating such rule based methodology into neural networks by embedding fuzzy inference systems into deep learning networks.

  11. 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.

  12. A Comparison of Neural, Fuzzy, Evolutionary, and Adaptive Approaches for Carrier Landing

    National Research Council Canada - National Science Library

    Steinberg, Marc

    2001-01-01

    .... The control law approaches examined are: fuzzy logic, two neural network approaches, indirect adaptive and non-adaptive versions of dynamic inversion, and a hybrid approach that combines direct and indirect adaptive elements...

  13. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-08-15

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

  15. Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach

    OpenAIRE

    Venus Marza; Amin Seyyedi; Luiz Fernando Capretz

    2008-01-01

    Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of Magnitude of Relative Error) applying neuro-fuzzy was substantially lower than M...

  16. 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.

  17. The Relevance of MCDM for Financial Decisions

    NARCIS (Netherlands)

    J. Spronk (Jaap); W.G.P.M. Hallerbach (Winfried)

    2002-01-01

    textabstractFor people working in finance, either in academia or in practice or in both, the combination of ?finance? and ?multiple criteria? is not obvious. However, we believe that many of the tools developed in the field of MCDM can contribute both to the quality of the financial economic

  18. Fuzzy multiple-criteria decision-making approach for industrial green engineering.

    Science.gov (United States)

    Chiou, Hua-kai; Tzeng, Gwo-hshiung

    2002-12-01

    This paper describes a fuzzy hierarchical analytic approach to determine the weighting of subjective judgments. In addition, it presents a nonadditive fuzzy integral technique to evaluate a green engineering industry case as a fuzzy multicriteria decision-making (FMCDM) problem. When the investment strategies are evaluated from various aspects, such as economic effectiveness, technical feasibility, and environmental regulation, it can be regarded as an FMCDM problem. Since stakeholders cannot clearly estimate each considered criterion in terms of numerical values for the anticipated alternatives/strategies, fuzziness is considered to be applicable. Consequently, this paper uses triangular fuzzy numbers to establish weights and anticipated achievement values. By ranking fuzzy weights and fuzzy synthetic utility values, we can determine the relative importance of criteria and decide the best strategies. This paper applies what is called a lambda fuzzy measure and nonadditive fuzzy integral technique to evaluate the synthetic performance of green engineering strategies for aquatic products processors in Taiwan. In addition, we demonstrate that the nonadditive fuzzy integral is an effective evaluation and appears to be appropriate, especially when the criteria are not independent.

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

    Directory of Open Access Journals (Sweden)

    R. Novin

    2017-11-01

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

  20. Diagnosis of Feedwater Heater Performance Degradation using Fuzzy Approach

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  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. Unsupervised approach data analysis based on fuzzy possibilistic clustering: application to medical image MRI.

    Science.gov (United States)

    El Harchaoui, Nour-Eddine; Ait Kerroum, Mounir; Hammouch, Ahmed; Ouadou, Mohamed; Aboutajdine, Driss

    2013-01-01

    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.

  3. 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.

  4. FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems

    Directory of Open Access Journals (Sweden)

    Levent Akin

    2008-11-01

    Full Text Available Finding optimal solutions to Partially Observable Markov Decision Problems is known to be NP-hard. This paper describes a novel neuro-fuzzy approach to obtain fast, robust and easily interpreted solutions by utilizing a combination of several learning techniques including neural networks, fuzzy decision making and Q-learning.

  5. FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems

    OpenAIRE

    Toygar Karadeniz; Levent Akin

    2004-01-01

    Finding optimal solutions to Partially Observable Markov Decision Problems is known to be NP-hard. This paper describes a novel neuro-fuzzy approach to obtain fast, robust and easily interpreted solutions by utilizing a combination of several learning techniques including neural networks, fuzzy decision making and Q-learning.

  6. FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems

    Directory of Open Access Journals (Sweden)

    Toygar Karadeniz

    2004-12-01

    Full Text Available Finding optimal solutions to Partially Observable Markov Decision Problems is known to be NP-hard. This paper describes a novel neuro-fuzzy approach to obtain fast, robust and easily interpreted solutions by utilizing a combination of several learning techniques including neural networks, fuzzy decision making and Q-learning.

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

    Indian Academy of Sciences (India)

    Otadi & Mosleh (2012) have applied a linear programming approach to find the non-negative solution of a fully fuzzy matrix equation whose elements of the coefficient matrix are considered as arbitrary triangular fuzzy numbers. There are no restrictions about the elements of the coefficient matrix of the corresponding system ...

  8. Double injection/single detection asymmetric flow injection manifold for spectrophotometric determination of ascorbic acid and uric acid: Selection the optimal conditions by MCDM approach based on different criteria weighting methods

    Science.gov (United States)

    Boroumand, Samira; Chamjangali, Mansour Arab; Bagherian, Ghadamali

    2017-03-01

    A simple and sensitive double injection/single detector flow injection analysis (FIA) method is proposed for the simultaneous kinetic determination of ascorbic acid (AA) and uric acid (UA). This method is based upon the difference between the rates of the AA and UA reactions with Fe3 + in the presence of 1, 10-phenanthroline (phen). The absorbance of Fe2 +/1, 10-phenanthroline (Fe-phen) complex obtained as the product was measured spectrophotometrically at 510 nm. To reach a good accuracy in the differential kinetic determination via the mathematical manipulations of the transient signals, different criteria were considered in the selection of the optimum conditions. The multi criteria decision making (MCDM) approach was applied for the selection of the optimum conditions. The importance weights of the evaluation criteria were determined using the analytic hierarchy process, entropy method, and compromised weighting (CW). The experimental conditions (alternatives) were ranked by the technique for order preference by similarity to an ideal solution. Under the selected optimum conditions, the obtained analytical signals were linear in the ranges of 0.50-5.00 and 0.50-4.00 mg L- 1 for AA and UA, respectively. The 3σ detection limits were 0.07 mg L- 1 for AA and 0.12 mg L- 1 for UA. The relative standard deviations for four replicate determinations of AA and UA were 2.03% and 3.30% respectively. The method was also applied for the analysis of analytes in the blood serum, Vitamine C tablets, and tap water with satisfactory results.

  9. 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.

  10. 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.

  11. 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.

  12. The fuzzy C spherical shells algorithm - A new approach

    Science.gov (United States)

    Krishnapuram, Raghu; Nasraoui, Olfa; Frigui, Hichem

    1992-01-01

    The fuzzy c spherical shells (FCSS) algorithm is specially designed to search for clusters that can be described by circular arcs or, more generally, by shells of hyperspheres. In this paper, a new approach to the FCSS algorithm is presented. This algorithm is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. An unsupervised algorithm which automatically finds the optimum number of clusters is also proposed. This algorithm can be used when the number of clusters is not known. It uses a cluster validity measure to identify good clusters, merges all compatible clusters, and eliminates spurious clusters to achieve the final result. Experimental results on several data sets are presented.

  13. 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 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...

  14. 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.

  15. The Economic Evaluation of Alternatives (EEoA): Rethinking the Application of Cost-effectiveness Analysis, Multi-criteria Decision-making (MCDM) and the Analysis of Alternatives (AoA) in Defense Procurement

    Science.gov (United States)

    2009-04-22

    MULTI-CRITERIA DECISION-MAKING ( MCDM ) AND THE ANALYSIS OF ALTERNATIVES (AOA) IN DEFENSE PROCUREMENT Published: 22 April 2009 by Dr. Francois Melese...Application of Cost-effectiveness Analysis, Multi-criteria Decision-making ( MCDM ) and the Analysis of Alternatives (AoA) in Defense Procurement 5a...study identifies a significant weakness in the Multicriteria Decision-making ( MCDM ) approach that currently underpins many contemporary AoAs. While

  16. Fuzzy optimization approach for the reliability of various schemes and fuzzy identification of weights in multicriteria optimization in control systems of nuclear reactors and power plants

    International Nuclear Information System (INIS)

    Zhuchkov, A.A.; Al'masri, Kh.F.

    2015-01-01

    An implementation of fuzzy optimization in the reliability of multicriteria selections in control schemes of nuclear reactors and power plants has been presented. In particular, optimization based on the theory of fuzzy sets has been proposed for the majority schemes, taking into account various reasons of failures. Set of fuzzy algorithms has been suggested as a basic technology for ranking process according to standard criterion, which includes steps of construction of the rules, initial estimation, fuzzification, and defuzzification. Software implementations have been presented for the fuzzy approach using the MatLab package [ru

  17. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    it is important to develop mathematical models and numerical procedures that would appropri- ately treat ... A general model for solving a fuzzy linear system whose coefficient matrix is crisp and the right hand side .... To represent the above problem as fully fuzzy linear system, we represent x as a quantity of the product 1 ...

  18. A new approach for studying fuzzy functional equations

    Directory of Open Access Journals (Sweden)

    Elias Deeba

    2001-01-01

    Full Text Available We define the concept of a “largest” and a “smallest” solution to an underlying equation and then show that a fuzzy solution of the corresponding fuzzy equation is bounded above and below by these solutions, respectively.

  19. Preference uncertainty in nonmarket valuation: a fuzzy approach

    NARCIS (Netherlands)

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

    2001-01-01

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

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

    Indian Academy of Sciences (India)

    http://www.ias.ac.in/article/fulltext/sadh/043/01/0003. Keywords. Transportation problem; multi-objective decision making; intuitionistic fuzzy programming; interval programming; goal programming. Abstract. Multi-objective transportation problem (MOTP) under intuitionistic fuzzy (IF) environment is analysed in this paper.

  1. Fuzzy set theoretic approach to fault tree analysis

    African Journals Online (AJOL)

    user

    events is replaced by possibilities, thereby leading to fuzzy fault tree analysis. Triangular and trapezoidal fuzzy numbers are used to represent the failure possibility of basic events. Since a system may have to go through different operating conditions during the design or testing phase. Thus the failure possibility of a basic ...

  2. 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.

  3. Applications of fuzzy decision making for personnel selection problem: A review

    Directory of Open Access Journals (Sweden)

    Afshari Reza Ali

    2014-01-01

    Full Text Available Personnel selection determines the input quality of personnel, therefore, plays a decisive role in human resource management. Personnel selection problem has been studied extensively. Selecting the best personnel among many alternatives is a multi-criteria decision making (MCDM problem. The necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy decision making along with their extensions have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Fuzzy decision making methods have become increasingly popular in decision making for personnel selection. Various decision making approaches have been proposed to solve the problem. This paper presents a comprehensive literature review of the applying Fuzzy decision making techniques in personnel selection problem.

  4. Querying Uncertain Data in Geospatial Object-relational Databases Using SQL and Fuzzy Sets

    Science.gov (United States)

    Ďuračiová, R.

    2013-12-01

    This paper deals with uncertainty modeling in spatial object-relational databases by the use of Structured Query Language (SQL). The fundamental principles of uncertainty modeling by fuzzy sets are applied in the area of geographic information systems (GIS) and spatial databases. A spatial database system includes types of spatial data and implements the spatial extension of SQL. The implementation of the principles of fuzzy logic to spatial databases brings an opportunity for the efficient processing of uncertain data, which is important, especially when using various data sources (e.g., multi-criteria decision making (MCDM) on the basis of heterogeneous spatial data resources). The modeling and data processing of uncertainties are presented in relation to the applicable International Organization for Standardization (ISO) standards (standards of the series 19100 Geographic information) and the relevant specifications of the Open Geospatial Consortium (OGC). The fuzzy spatial query approach is applied and tested on a case study with a fundamental database for GIS in Slovakia.

  5. Strategic Part Prioritization for Quality Improvement Practice Using a Hybrid MCDM Framework: A Case Application in an Auto Factory

    Directory of Open Access Journals (Sweden)

    Fuli Zhou

    2016-06-01

    Full Text Available Quality improvement practice (QIP, as a competitive strategy, is increasingly vital for auto factories to improve the product quality and brand reputation. Quality activity on selected automotive parts among a variety of competing candidates is featured by prioritization calculation. It arouses our interest how to select the appropriate auto part to perform quality improvement action based on the collected data from the after-sale source. Managers usually select the QIP part by the rule of thumb that is based on the quantitative criterion or the subjective preference of individuals. The total quality management (TQM philosophy requires multiple stakeholders’ involvement, regarded as a multi-criteria decision making (MCDM issue. This paper proposes a novel hybrid MCDM framework to select the best quality improvement solution combining the subjective and objective information. The rough set-based attribute reduction (RSAR technique was employed to establish the hierarchy structure of influential criteria, and the decision information was collected with triangular fuzzy numbers (TFNs for its vagueness and ambiguity. In addition, the novel hybrid MCDM framework integrating fuzzy DEMATEL (decision making trial and evaluation laboratory method, the anti-entropy weighting (AEW technique and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR was developed to rank the alternatives with the combined weight of criteria. The results argue that the optimal solution keeps a high conformance with Shemshadi’s and Chaghooshi’s methods, which is better than the existing determination. Besides, the result analysis shows the robustness and flexibility of the proposed hybrid MCDM framework.

  6. Integrated Evaluation of Urban Water Bodies for Pollution Abatement Based on Fuzzy Multicriteria Decision Approach

    Science.gov (United States)

    Hashim, Sarfraz; Yuebo, Xie; Saifullah, Muhammad; Nabi Jan, Ramila; Muhetaer, Adila

    2015-01-01

    Today's ecology is erected with miscellaneous framework. However, numerous sources deteriorate it, such as urban rivers that directly cause the environmental pollution. For chemical pollution abatement from urban water bodies, many techniques were introduced to rehabilitate the water quality of these water bodies. In this research, Bacterial Technology (BT) was applied to urban rivers escalating the necessity to control the water pollution in different places (Xuxi River (XXU); Gankeng River (GKS); Xia Zhang River (XZY); Fenghu and Song Yang Rivers (FSR); Jiu Haogang River (JHH)) in China. For data analysis, the physiochemical parameters such as temperature, chemical oxygen demand (COD), dissolved oxygen (DO), total phosphorus (TP), and ammonia nitrogen (NH3N) were determined before and after the treatment. Multicriteria Decision Making (MCDM) method was used for relative significance of different water quality on each station, based on fuzzy analytical hierarchy process (FAHP). The overall results revealed that the pollution is exceeding at “JHH” due to the limit of “COD” as critical water quality parameter and after treatment, an abrupt recovery of the rivers compared with the average improved efficiency of nutrients was 79%, 74%, 68%, and 70% of COD, DO, TP, and NH3N, respectively. The color of the river's water changed to its original form and aquatic living organism appeared with clear effluents from them. PMID:26516623

  7. Representing a new approach for implementing e-insurance using fuzzy DEMATEL

    Directory of Open Access Journals (Sweden)

    Mahsa Shahhosseini

    2013-02-01

    Full Text Available During the past two decades, e-commerce has revolutionized many industries by providing easy access infrastructures for interested users who wish to place their orders via internet facilities. Insurance industry is one of the most important financial industries in the world. E-commerce has been attracting many in insurance industry and insurance industry has utilized e-commerce because of its own significance in economic growth and health of society. However, enhancing e-commerce into insurance firms may face serious barriers and it is important to detect and setup appropriate actions to remove them. In this paper, we present a multi-criteria decision making (MCDM technique based on DEMATEL with an adaptation of fuzzy logic to find important factors influencing implementation of e-commerce into insurance industry. The proposed study of this paper designs a questionnaire and distributes it among five important insurance experts. Findings indicate that “behavioral-cultural barriers” influence on structural and field barriers. “Problems resulted from obeying government complicated rules” in the group of structural barriers, “low capacity of accepting e-insurance” in field barriers group and “lack of sufficient support of insurance chief managers from e-insurance and relative tendency of insurance staffs to make the insurance affairs electronic” in behavioral-cultural barriers group have the most influence on other factors of group.

  8. Integrated Evaluation of Urban Water Bodies for Pollution Abatement Based on Fuzzy Multicriteria Decision Approach.

    Science.gov (United States)

    Hashim, Sarfraz; Yuebo, Xie; Saifullah, Muhammad; Nabi Jan, Ramila; Muhetaer, Adila

    2015-01-01

    Today's ecology is erected with miscellaneous framework. However, numerous sources deteriorate it, such as urban rivers that directly cause the environmental pollution. For chemical pollution abatement from urban water bodies, many techniques were introduced to rehabilitate the water quality of these water bodies. In this research, Bacterial Technology (BT) was applied to urban rivers escalating the necessity to control the water pollution in different places (Xuxi River (XXU); Gankeng River (GKS); Xia Zhang River (XZY); Fenghu and Song Yang Rivers (FSR); Jiu Haogang River (JHH)) in China. For data analysis, the physiochemical parameters such as temperature, chemical oxygen demand (COD), dissolved oxygen (DO), total phosphorus (TP), and ammonia nitrogen (NH3N) were determined before and after the treatment. Multicriteria Decision Making (MCDM) method was used for relative significance of different water quality on each station, based on fuzzy analytical hierarchy process (FAHP). The overall results revealed that the pollution is exceeding at "JHH" due to the limit of "COD" as critical water quality parameter and after treatment, an abrupt recovery of the rivers compared with the average improved efficiency of nutrients was 79%, 74%, 68%, and 70% of COD, DO, TP, and NH3N, respectively. The color of the river's water changed to its original form and aquatic living organism appeared with clear effluents from them.

  9. Integrated Evaluation of Urban Water Bodies for Pollution Abatement Based on Fuzzy Multicriteria Decision Approach

    Directory of Open Access Journals (Sweden)

    Sarfraz Hashim

    2015-01-01

    Full Text Available Today’s ecology is erected with miscellaneous framework. However, numerous sources deteriorate it, such as urban rivers that directly cause the environmental pollution. For chemical pollution abatement from urban water bodies, many techniques were introduced to rehabilitate the water quality of these water bodies. In this research, Bacterial Technology (BT was applied to urban rivers escalating the necessity to control the water pollution in different places (Xuxi River (XXU; Gankeng River (GKS; Xia Zhang River (XZY; Fenghu and Song Yang Rivers (FSR; Jiu Haogang River (JHH in China. For data analysis, the physiochemical parameters such as temperature, chemical oxygen demand (COD, dissolved oxygen (DO, total phosphorus (TP, and ammonia nitrogen (NH3N were determined before and after the treatment. Multicriteria Decision Making (MCDM method was used for relative significance of different water quality on each station, based on fuzzy analytical hierarchy process (FAHP. The overall results revealed that the pollution is exceeding at “JHH” due to the limit of “COD” as critical water quality parameter and after treatment, an abrupt recovery of the rivers compared with the average improved efficiency of nutrients was 79%, 74%, 68%, and 70% of COD, DO, TP, and NH3N, respectively. The color of the river’s water changed to its original form and aquatic living organism appeared with clear effluents from them.

  10. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hu-Chen [School of Management, Hefei University of Technology, Hefei 230009 (China); Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552 (Japan); Wu, Jing [Department of Public Management, Tongji University, Shanghai 200092 (China); Li, Ping, E-mail: yiwuchulp@126.com [Shanghai Pudong New Area Zhoupu Hospital, No. 135 Guanyue Road, Shanghai 201318 (China); East Hospital Affiliated to Tongji University, No. 150 Jimo Road, Shanghai 200120 (China)

    2013-12-15

    Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.

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

    OpenAIRE

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

    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...

  12. 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.

  13. Application of fuzzy TOPSIS and generalized Choquet integral methods to select the best supplier

    Directory of Open Access Journals (Sweden)

    Aytac Yildiz

    2017-04-01

    Full Text Available Supplier selection is a complex multi-criteria decision making (MCDM problem. There are literally various methods for choosing appropriate supplier but there are several criteria involved in complex decision making process. The classical MCDM methods cannot effectively solve real-world problems however fuzzy MCDM methods facilitate the solution fairly and enable the decision-makers to reach accurate decisions in this selection process. In this study, a supplier selection problem is handled, in a firm in automotive industry of Turkey. Fuzzy TOPSIS (Technique for Order Performance by Similarity to Ideal Solution and generalized Choquet integral are used individually in the solution of the problem.

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

    International Nuclear Information System (INIS)

    Shaw, W.; Grindrod, P.

    1989-01-01

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

  15. 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.

  16. Interaction between the written procedure and the technician: a fuzzy modeling approach

    International Nuclear Information System (INIS)

    More, Jesus Domech; Tansheit, Ricardo

    2005-01-01

    This paper deals with an application of fuzzy numbers to the interaction between the written procedure and the technician during inspection. The techniques based on fuzzy set theory are appropriate tools for the treatment of subjective and vague concepts that are inherent to system reliability. The application consists of an analysis through fuzzy probability and through a failure possibility concept, which is a subjective unreliability measure. This approach allows the use of natural language expressions of reliability estimation. It is shown which events (human actions) should be focused on during training and practice in order to improve the above mentioned interaction. (author)

  17. 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.

  18. 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.

  19. 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.

  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 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...

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

    Directory of Open Access Journals (Sweden)

    CHERNOV Vladimir

    2018-01-01

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

  3. 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...

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

    International Nuclear Information System (INIS)

    Ghyym, Seong Ho

    1998-01-01

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

  5. An Approach to Evaluate the Clothing Creative Design with Dual Hesitant Fuzzy Information

    Directory of Open Access Journals (Sweden)

    Ya-Mei Li

    2014-01-01

    Full Text Available The problem of evaluating the clothing creative design with dual hesitant fuzzy information is the multiple attribute decision making problem. In this paper, we have utilized dual hesitant fuzzy hybrid average (DHFHA operator to develop the model to solve the multiple attribute decision making problems for evaluating the clothing creative design. Finally, a practical example for evaluating the clothing creative design is given to verify the developed approach.

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

    Directory of Open Access Journals (Sweden)

    C. K. Kwong

    2013-01-01

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

  8. Supporting sustainable electricity technologies in Greece using MCDM

    Energy Technology Data Exchange (ETDEWEB)

    Doukas, H.; Patlitzianas, K.D.; Psarras, J. [National Technical Univ., Athens (Greece). School of Electrical and Computer Engineering

    2006-06-15

    The penetration of sustainable technologies in electricity generation is low until now in Greece. However, the recent adoption of legislative rules towards the effective operation of liberalized markets, as well as the increased impact of climate change on the electricity sector towards the period 2008-2012, bring out these technologies as key means for establishing conditions of security, stability and environmental protection. The objective of this paper is to put on the map the sustainable technologies for electricity generation in Greece through the formulation of a collective interactive supportive framework, using an existing multi-criteria decision-making (MCDM) method to elaborate more realistic and transparent outcomes. The approach was implemented under the umbrella of the national Foresight Programme, to assist policy making for sustainable electricity generation technologies. [Author].

  9. A new approach for automatic control modeling, analysis and design in fully fuzzy environment

    Directory of Open Access Journals (Sweden)

    Walaa Ibrahim Gabr

    2015-09-01

    Full Text Available The paper presents a new approach for the modeling, analysis and design of automatic control systems in fully fuzzy environment based on the normalized fuzzy matrices. The approach is also suitable for determining the propagation of fuzziness in automatic control and dynamical systems where all system coefficients are expressed as fuzzy parameters. A new consolidity chart is suggested based on the recently newly developed system consolidity index for testing the susceptibility of the system to withstand changes due to any system or input parameters changes effects. Implementation procedures are elaborated for the consolidity analysis of existing control systems and the design of new ones, including systems comparisons based on such implementation consolidity results. Application of the proposed methodology is demonstrated through illustrative examples, covering fuzzy impulse response of systems, fuzzy Routh–Hurwitz stability criteria, fuzzy controllability and observability. Moreover, the use of the consolidity chart for the appropriate design of control system is elaborated through handling the stabilization of inverted pendulum through pole placement technique. It is also shown that the regions comparison in consolidity chart is based on type of consolidity region shape such as elliptical or circular, slope or angle in degrees of the centerline of the geometric shape, the centroid of the geometric shape, area of the geometric shape, length of principal diagonals of the shape, and the diversity ratio of consolidity points for each region. Finally, it is recommended that the proposed consolidity chart approach be extended as a unified theory for modeling, analysis and design of continuous and digital automatic control systems operating in fully fuzzy environment.

  10. A Neuro-Fuzzy Approach in the Classification of Students' Academic Performance

    Science.gov (United States)

    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. PMID:24302928

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

    Directory of Open Access Journals (Sweden)

    Bojana Jovanović

    2014-10-01

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

  12. A 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.

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

    Science.gov (United States)

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

    2006-04-01

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

  14. 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.

  15. A Fuzzy Linear Programming Approach for Aggregate Production Planning

    DEFF Research Database (Denmark)

    Iris, Cagatay; Cevikcan, Emre

    2014-01-01

    Aggregate Production Planning (APP) is considered as an important stage in production systems, since it links operations with strategies and plays a key role in enterprise resource planning and organizational integration. An effective APP should not only provide the minimization of production...... and inventory costs, but also increase the level of service available to the customers. When maintaining APP, some of cost and demand parameters cannot be frequently determined as crisp values. Fuzzy logic is utilized in many engineering applications so as to handle imprecise data. This chapter provides...... 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. Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

    Science.gov (United States)

    Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

    2018-02-01

    As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

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

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2012-01-01

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

  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. Fuzzy neural network approaches for robotic gait synthesis.

    Science.gov (United States)

    Juang, J G

    2000-01-01

    In this paper, a learning scheme using a fuzzy controller to generate walking gaits is developed. The learning scheme uses a fuzzy controller combined with a linearized inverse biped model. The controller provides the control signals at each control time instant. The algorithm used to train the controller is "backpropagation through time". The linearized inverse biped model provides the error signals for backpropagation through the controller at control time instants. Given prespecified constraints such as the step length, crossing clearance, and walking speed, the control scheme can generate the gait that satisfies these constraints. Simulation results are reported for a five-link biped robot.

  20. 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.

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

    Science.gov (United States)

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

    2012-04-30

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

  2. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

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

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

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2007-01-01

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

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

    African Journals Online (AJOL)

    Research in conventional fault tree analysis (FTA) is based mainly on failure probability of basic events, which uses classical probability distributions for the failure probability of basic events. In the present paper the probabilistic consideration of basic events is replaced by possibilities, thereby leading to fuzzy fault tree ...

  6. A genetic-based neuro-fuzzy approach for modeling and control of dynamical systems.

    Science.gov (United States)

    Farag, W A; Quintana, V H; Lambert-Torres, G

    1998-01-01

    Linguistic modeling of complex irregular systems constitutes the heart of many control and decision making systems, and fuzzy logic represents one of the most effective algorithms to build such linguistic models. In this paper, a linguistic (qualitative) modeling approach is proposed. The approach combines the merits of the fuzzy logic theory, neural networks, and genetic algorithms (GA's). The proposed model is presented in a fuzzy-neural network (FNN) form which can handle both quantitative (numerical) and qualitative (linguistic) knowledge. The learning algorithm of an FNN is composed of three phases. The first phase is used to find the initial membership functions of the fuzzy model. In the second phase, a new algorithm is developed and used to extract the linguistic-fuzzy rules. In the third phase, a multiresolutional dynamic genetic algorithm (MRD-GA) is proposed and used for optimized tuning of membership functions of the proposed model. Two well-known benchmarks are used to evaluate the performance of the proposed modeling approach, and compare it with other modeling approaches.

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  8. An MCDM for a Large Set of Criteria

    Science.gov (United States)

    2009-10-01

    RTO-MP-SAS-080 18 - 1 An MCDM for a Large Set of Criteria Dr. Hilja Lisa Huru and M.Sc. Erlend Hoff Norwegian Defence Research...control number. 1. REPORT DATE OCT 2009 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE An MCDM for a Large Set of Criteria 5a...unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 An MCDM for a Large Set of Criteria 18

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

    Science.gov (United States)

    Kiss, Andrea; Viglione, Alberto; Viertl, Reinhard; Blöschl, Günter

    2016-01-01

    Abstract 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. PMID:27840456

  10. 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

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

    International Nuclear Information System (INIS)

    Iliev, Atanas M.

    2003-01-01

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

  12. 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.

  13. Modified risk graph method using fuzzy rule-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Nait-Said, R., E-mail: r_nait_said@hotmail.com [LARPI Laboratory, Safety Department, Institute of Health and Occupational Safety, University of Batna, Road Med El-Hadi Boukhlouf, Batna (Algeria); Zidani, F., E-mail: fati_zidani@lycos.com [LSPIE Laboratory, Electrical Engineering Department, Faculty of Engineering, University of Batna, Road Med El-Hadi Boukhlouf, Batna 05000 (Algeria); Ouzraoui, N., E-mail: ouzraoui@yahoo.fr [LARPI Laboratory, Safety Department, Institute of Health and Occupational Safety, University of Batna, Road Med El-Hadi Boukhlouf, Batna (Algeria)

    2009-05-30

    The risk graph is one of the most popular methods used to determine the safety integrity level for safety instrumented functions. However, conventional risk graph as described in the IEC 61508 standard is subjective and suffers from an interpretation problem of risk parameters. Thus, it can lead to inconsistent outcomes that may result in conservative SILs. To overcome this difficulty, a modified risk graph using fuzzy rule-based system is proposed. This novel version of risk graph uses fuzzy scales to assess risk parameters and calibration may be made by varying risk parameter values. Furthermore, the outcomes which are numerical values of risk reduction factor (the inverse of the probability of failure on demand) can be compared directly with those given by quantitative and semi-quantitative methods such as fault tree analysis (FTA), quantitative risk assessment (QRA) and layers of protection analysis (LOPA).

  14. Modified risk graph method using fuzzy rule-based approach.

    Science.gov (United States)

    Nait-Said, R; Zidani, F; Ouzraoui, N

    2009-05-30

    The risk graph is one of the most popular methods used to determine the safety integrity level for safety instrumented functions. However, conventional risk graph as described in the IEC 61508 standard is subjective and suffers from an interpretation problem of risk parameters. Thus, it can lead to inconsistent outcomes that may result in conservative SILs. To overcome this difficulty, a modified risk graph using fuzzy rule-based system is proposed. This novel version of risk graph uses fuzzy scales to assess risk parameters and calibration may be made by varying risk parameter values. Furthermore, the outcomes which are numerical values of risk reduction factor (the inverse of the probability of failure on demand) can be compared directly with those given by quantitative and semi-quantitative methods such as fault tree analysis (FTA), quantitative risk assessment (QRA) and layers of protection analysis (LOPA).

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

    OpenAIRE

    M.A. Lazim; M. Suriani

    2009-01-01

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

  16. 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.  

  17. Linear programming approach to matrix games with intuitionistic fuzzy goals

    Directory of Open Access Journals (Sweden)

    Jiang-Xia Nan

    2013-02-01

    Full Text Available Adding an additional degree of non-membership, K. T. Atanassov introduced the concept of the intuitionistic fuzzy (IF set (IF-set, which has rarely been applied to the game theory yet. The aim of this paper is to develop the concept and methodology of matrix games with IF-set goals in which goals of players are expressed with IF-sets and payoffs are expressed with real numbers rather than IF-sets. In this methodology, the concepts of IF-set goals and the solutions of matrix games with IF-set goals are proposed. It is proven that solutions of matrix games with IF-set goals can be obtained through solving the developed auxiliary linear programming models, which are the generalization of matrix games with fuzzy goals. The proposed methodology is illustrated with a numerical example. Furthermore, comparison analysis of the proposed methodology is conducted to show its advantages over matrix games with fuzzy goals.

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

    Science.gov (United States)

    Narayanamoorthy, S; Sathiyapriya, S P

    2016-01-01

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

  19. Identification of drought in Dhalai river watershed using MCDM and ...

    Indian Academy of Sciences (India)

    Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, ...

  20. SISTEM PENDUKUNG KEPUTUSAN DENGAN METODA MULTI-CRITERIA DECISION MAKING ( MCDM

    Directory of Open Access Journals (Sweden)

    Nur Heri Cahyana

    2015-04-01

    Full Text Available Multicriteria decision making methods MCDM technique takes preference to the  idealsolution, TOPSIS is one of the more widely used MCDM methods in decision supportsystems. For the purpose of the work, the modified TOPSIS method into a form that canbe used for the implementation of web-based medical diagnosis system. In modifying TOPSIS method,  we utilize fuzzy logic te so users can more accurately describe their symptoms. Data provided by the modified TOPSIS method is often in proportion and maytake considerable time to produce alternative rankings. TOPSIS is suitable for parallel computing due to a combination of  matrix calculations. Therefore implemented a parallelcomputer so that a large number of input data can be handled simultaneously, it reduces the overall execution time. In addition, making the system more accessible MCDM. Web-based medical diagnosis system including user interface dynamically generated.

  1. Construction of Fuzzy Ontologies from Fuzzy UML Models

    Directory of Open Access Journals (Sweden)

    Fu Zhang

    2013-05-01

    Full Text Available The success and proliferation of the Semantic Web depends heavily on construction of Web ontologies. However, classical ontology construction approaches are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. Therefore, great efforts on construction of fuzzy ontologies have been made in recent years. In this paper, we propose a formal approach and develop an automated tool for constructing fuzzy ontologies from fuzzy UML models. , we propose formalization methods of fuzzy UML models and fuzzy ontologies, where fuzzy UML models and fuzzy ontologies can be represented and interpreted by their respective formal definitions and semantic interpretation methods. , we propose an approach for constructing fuzzy ontologies from fuzzy UML models, i.e., transforming fuzzy UML models (including the structure and instance information of fuzzy UML models into fuzzy ontologies. , following the proposed approach, we implement a prototype transformation tool called that can construct fuzzy ontologies from fuzzy UML models. Constructing fuzzy ontologies from fuzzy UML models will facilitate the development of Web ontologies. , in order to show that the constructed fuzzy ontologies may be useful for reasoning on fuzzy UML models, we investigate how to reason on fuzzy UML models based on the constructed fuzzy ontologies, and it turns out that the reasoning tasks of fuzzy UML models can be checked by means of the reasoning mechanism of fuzzy ontologies.

  2. 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.

  3. 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.

  4. Application of fuzzy AHP method to IOCG prospectivity mapping: A case study in Taherabad prospecting area, eastern Iran

    Science.gov (United States)

    Najafi, Ali; Karimpour, Mohammad Hassan; Ghaderi, Majid

    2014-12-01

    Using fuzzy analytical hierarchy process (AHP) technique, we propose a method for mineral prospectivity mapping (MPM) which is commonly used for exploration of mineral deposits. The fuzzy AHP is a popular technique which has been applied for multi-criteria decision-making (MCDM) problems. In this paper we used fuzzy AHP and geospatial information system (GIS) to generate prospectivity model for Iron Oxide Copper-Gold (IOCG) mineralization on the basis of its conceptual model and geo-evidence layers derived from geological, geochemical, and geophysical data in Taherabad area, eastern Iran. The FuzzyAHP was used to determine the weights belonging to each criterion. Three geoscientists knowledge on exploration of IOCG-type mineralization have been applied to assign weights to evidence layers in fuzzy AHP MPM approach. After assigning normalized weights to all evidential layers, fuzzy operator was applied to integrate weighted evidence layers. Finally for evaluating the ability of the applied approach to delineate reliable target areas, locations of known mineral deposits in the study area were used. The results demonstrate the acceptable outcomes for IOCG exploration.

  5. Data-Based Fuzzy TOPSIS for Alternative Ranking

    Directory of Open Access Journals (Sweden)

    Victor Utomo

    2016-01-01

    Full Text Available Technique for Order Preference by Similarity (TOPSIS solves multi-criteria decision making (MCDM by ranking the alternatives. When the attributes are not deterministic, a Fuzzy TOPSIS method is applied. The traditional fuzzy TOPSIS depends on decision makers to determine alternative’s value which considered subjective. A new method named data-based fuzzy TOPSIS proposed to diminish the dependency to decision maker. The proposed algorithm use data to determine alternative’s values objectively. Subtractive Clustering (SC and Fuzzy C-Mean (FCM selected to transform crisp value data to fuzzy value data. Some modification applied to SC and FCM to obtain fuzzy triangular value needed by fuzzy TOPSIS.  Keyword : Index Terms—Decision support systems,  fuzzy TOPSIS, fuzzy C-mean, subtractive clustering

  6. 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

  7. Occupational musculoskeletal disorders management using Fuzzy TOPSIS Assessment of Repetitive Tasks (ART).

    Science.gov (United States)

    Khandan, M; Koohpaei, A R; Nili, M; Farjami, Y

    2017-01-01

    In order to evaluate occupational disorders and ergonomic problems in a workplace, Multiple Criteria Decision Making (MCDM) problem solving methods such as Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be utilized. In this paper, Musculoskeletal Disorder (MSD) risk factors were evaluated in a manufacturing company in Iran by a method called Assessment of Repetitive Tasks (ART) of the upper limbs integrated with Fuzzy TOPSIS in order to prioritize the corrective actions. This study was done with a descriptive-analytical approach. The company under study had 240 employees who were working in seven different shops. Out of all tasks, 13 tasks were included in the study. Required information was gathered by a demographic questionnaire and ART method. Also, Fuzzy TOPSIS was utilized for the prioritization of the company shops based on the ergonomic control needs. Data analysis from ART indicated that 74.6% of the reviewed tasks were high risk. Based on the F- TOPSIS-ART results, Production shop prioritized as the highest need for MSD control. Because there is time and financial resources limit in ergonomic control activities, a fuzzy prioritization approach such as Fuzzy TOPSIS ART can be used to take advantage of the available resources and control risks to as low as reasonably practicable (ALARP) level.

  8. Fuzzy Supervisor Approach Design Based-Switching Controller for Pumping Station: Experimental Validation

    Directory of Open Access Journals (Sweden)

    Wael Chakchouk

    2017-01-01

    Full Text Available This paper proposes a discrete-time switching controller strategy for a hydraulic process pumping station. The proposed solution leads to improving control system performances with two tests: combination of Fuzzy-PD and PI controllers and Fuzzy-PID and PI controllers. The proposed design methodology is based on accurate model for pumping station (PS, which is developed in previous works using Fuzzy-C Means (FCM algorithm. The control law design is based on switching control; a fuzzy supervisor manages the switching from one to another and regulates the rate of participation of each order, in order to satisfy various objectives of a stable pumping station like the asymptotic stability of the tracking error. To validate the proposed solution, experimental tests are made and analyzed. Compared to the conventional PI and fuzzy logic (FL approaches, the results show that the switching controller allows exhibiting excellent transient response over a wide range of operating conditions and especially is easier to be implemented in practice.

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

    Directory of Open Access Journals (Sweden)

    Ayad Hendalianpour

    2016-11-01

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

  10. 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.

  11. 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)

  12. 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...

  13. A new approach to the detection of lesions in mammography using fuzzy clustering.

    Science.gov (United States)

    Wang, Y; Shi, H; Ma, S

    2011-01-01

    Breast cancer is a leading cause of female mortality and its early detection is an important means of reducing this. The present study investigated an approach, based on fuzzy clustering, to detect small lesions, such as microcalcifications and other masses, that are hard to recognize in breast cancer screening. A total of 180 mammograms were analysed and classified by radiologists into three groups (n = 60 per group): those with microcalcifications; those with tumours; and those with no lesions. Twenty mammograms were taken as training data sets from each of the groups. The algorithm was then applied to the data not taken for training. Analysis by fuzzy clustering achieved a mean accuracy of 99.7% compared with the radiologists' findings. It was concluded that the fuzzy clustering algorithm allowed for more efficient and accurate detection of breast lesions and may improve the early detection of breast tumours.

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

    Directory of Open Access Journals (Sweden)

    Sohrab Kordrostami

    2016-07-01

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

  15. Using the fuzzy majority approach for GIS-based multicriteria group decision-making

    Science.gov (United States)

    Boroushaki, Soheil; Malczewski, Jacek

    2010-03-01

    This paper is concerned with developing a framework for GIS-based multicriteria group decision-making using the fuzzy majority approach. The procedure for solving a spatial group decision-making problem involves two stages. First, each decision-maker solves the problem individually. Second, the individual solutions are aggregated to obtain a group solution. The first stage is operationalized by a linguistic quantifier-guided ordered weighted averaging (OWA) procedure to create individual decision-maker's solution maps. Then the individual maps are combined using the fuzzy majority procedure to generate the group solution map which synthesizes the majority of the decision-makers' preferences. The paper provides an illustrative example of the fuzzy majority method for a land suitability problem. It also demonstrates the implementation of the framework within the ArcGIS environment.

  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. 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.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  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. Optimization approach for saddling cost of medical cyclotrons with fuzziness

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  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. 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

  3. Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

    Science.gov (United States)

    Choudhuri, P. K.

    2014-12-01

    Multi-Criteria Decision Making is a branch of Operation Research (OR) having a comparatively short history of about 40 years. It is being popularly used in the field of engineering, banking, fixing policy matters etc. It can also be applied for taking decisions in daily life like selecting a car to purchase, selecting bride or groom and many others. Various MCDM methods namely Weighted Sum Model (WSM), Weighted Product Model (WPM), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) and Elimination and Choice Translating Reality (ELECTRE) are there to solve many decision making problems, each having its own limitations. However it is very difficult to decide which MCDM method is the best. MCDM methods are prospective quantitative approaches for solving decision problems involving finite number of alternatives and criteria. Very few research works in textiles have been carried out with the help of this technique particularly where decision taking among several alternatives becomes the major problem based on some criteria which are conflicting in nature. Gradation of jute fibres on the basis of the criteria like strength, root content, defects, colour, density, fineness etc. is an important task to perform. The MCDM technique provides enough scope to be applied for the gradation of jute fibres or ranking among several varieties keeping in view a particular object and on the basis of some selection criteria and their relative weightage. The present paper is an attempt to explore the scope of applying the multiplicative AHP method of multi-criteria decision making technique to determine the quality values of selected jute fibres on the basis of some above stated important criteria and ranking them accordingly. A good agreement in ranking is observed between the existing Bureau of Indian Standards (BIS) grading and proposed method.

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

    Directory of Open Access Journals (Sweden)

    Peng Wang

    2015-01-01

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

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

    International Nuclear Information System (INIS)

    Baser, Furkan; Demirhan, Haydar

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-11-01

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

  7. 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.

  8. Fuzzy Goal Programming Approach in Selective Maintenance Reliability Model

    Directory of Open Access Journals (Sweden)

    Neha Gupta

    2013-12-01

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

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    M.S. Osman

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Mohsen Gharakhani

    2013-01-01

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

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

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

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

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

    International Nuclear Information System (INIS)

    Peche, Roberto; Rodriguez, Esther

    2009-01-01

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

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

    International Nuclear Information System (INIS)

    Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein

    2006-01-01

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

  17. Risk assessment of groundwater contamination: a multilevel fuzzy comprehensive evaluation approach based on DRASTIC model.

    Science.gov (United States)

    Zhang, Qiuwen; Yang, Xiaohong; Zhang, Yan; Zhong, Ming

    2013-01-01

    Groundwater contamination is a serious threat to water supply. Risk assessment of groundwater contamination is an effective way to protect the safety of groundwater resource. Groundwater is a complex and fuzzy system with many uncertainties, which is impacted by different geological and hydrological factors. In order to deal with the uncertainty in the risk assessment of groundwater contamination, we propose an approach with analysis hierarchy process and fuzzy comprehensive evaluation integrated together. Firstly, the risk factors of groundwater contamination are identified by the sources-pathway-receptor-consequence method, and a corresponding index system of risk assessment based on DRASTIC model is established. Due to the complexity in the process of transitions between the possible pollution risks and the uncertainties of factors, the method of analysis hierarchy process is applied to determine the weights of each factor, and the fuzzy sets theory is adopted to calculate the membership degrees of each factor. Finally, a case study is presented to illustrate and test this methodology. It is concluded that the proposed approach integrates the advantages of both analysis hierarchy process and fuzzy comprehensive evaluation, which provides a more flexible and reliable way to deal with the linguistic uncertainty and mechanism uncertainty in groundwater contamination without losing important information.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Daniel Manaţe

    2015-01-01

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

  20. 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.

  1. A weighted possibilistic programming approach for sustainable vendor selection and order allocation in fuzzy environment

    DEFF Research Database (Denmark)

    Gupta, Pankaj; Govindan, Kannan; Mehlawat, Mukesh Kumar

    2016-01-01

    This paper focused on the analysis of imprecise information in terms of many critical parameters for a multi-objective multi-item vendor selection-order allocation problem with price-breaks. We used both quantitative and qualitative criteria taking into account the economic, technological, social......, environmental factors, and the price-breaks that were offered on order quantity following ‘all-unit discount schedule.’ We developed an optimization model that integrated fuzzy multi-objective integer linear programming and analytic hierarchy process techniques. A weighted possibilistic programming approach...... approach were tested on the data set of an industrial case study. A detailed performance analysis and comparisons were done to show superiority of the proposed methodology over the existing related fuzzy programming approaches....

  2. A Fuzzy-Neural Ensemble and Geometric Rule Fusion Approach for Scheduling a Wafer Fabrication Factory

    Directory of Open Access Journals (Sweden)

    Hsin-Chieh Wu

    2013-01-01

    Full Text Available In this study, the fuzzy-neural ensemble and geometric rule fusion approach is presented to optimize the performance of job dispatching in a wafer fabrication factory with an intelligent rule. The proposed methodology is a modification of a previous study by fusing two dispatching rules and diversifying the job slacks in novel ways. To this end, the geometric mean of the neighboring distances of slacks is maximized. In addition, the fuzzy c-means (FCM and backpropagation network (BPN ensemble approach was also proposed to estimate the remaining cycle time of a job, which is an important input to the new rule. A new aggregation mechanism was also designed to enhance the robustness of the FCM-BPN ensemble approach. To validate the effectiveness of the proposed methodology, some experiments have been conducted. The experimental results did support the effectiveness of the proposed methodology.

  3. 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.

  4. Fuzzy approach to innovative programs development in conditions of partial and full uncertainty

    Directory of Open Access Journals (Sweden)

    CHERNOV Vladimir

    2017-01-01

    Full Text Available In the article the authors develop their research aimed at the use of fuzzy logic and fuzzy set theory to model the solution of economic problems. In particular, there are considered approaches to formation of innovative programs and the choice of a set of innovative projects, and their components, under varying degrees of uncertainty. Among the major selection criteria were identified such as financial capacity, payback period, profitability, social significance, regulatory compliance, degree of novelty, size of the market, opportunity of international cooperation, financing flexibility, flexibility of project and others. Algorithms using fuzzy linguistic expert assessment of the main criteria that characterize the innovative programs are proposed. At the same time can be taken into account the level of competence of experts as well as the requirements of the regional authorities and the degree of uncertainty. The proposed solutions are based on the multicriteria convolutions of criteria estimates, max-min approach and computational analysis of the relations of domination. Are given examples of calculations for the pessimistic and optimistic approaches to the solution. Also described approach of rigorous dominance, interval dominance and not dominance in the case of considerable uncertainty, allows establish the relative degree of efficiency and a measure of preference for several innovative projects. The described theoretical approach can be successfully extended to other situations need formalized solving of multicriterial choice problems on the set of alternatives in conditions of different degrees of uncertainty in the economy.

  5. An approach to the fuzzy variable structure control of induction motors

    International Nuclear Information System (INIS)

    Barazane, L.; Krishan, M.M.; Khwaldeh, A.; Sicard, P.

    2008-01-01

    This paper concerns fuzzy sliding mode control. A new approach, which was first introduced by Ben-Ghalia et al., is applied to the cascade sliding mode control of an induction motor fed by a PWM voltage source inverter, which operates in a fixed reference frame. For this purpose, a new decoupled and reduced model is first proposed. Then, a set of simple surfaces and associated control laws are synthesized. A piecewise smooth control function with a threshold is adopted. However, the magnitude of this function depends closely on the upper bound of uncertainties, which include parameter variations and external disturbances. This bound is difficult to obtain prior to motor operation. To solve this problem, a new fuzzy sliding mode control applied to an induction motor drive is presented. The fuzzy sliding mode controllers are designed in order to improve the control performances and to reduce the control energy and the chattering phenomenon. Simulation results reveal some very interesting features and show that the proposed fuzzy sliding mode controller could be considered as an alternative to the conventional sliding mode controllers of induction motors. (author)

  6. 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.

  7. Fuzzy Boundary and Fuzzy Semiboundary

    OpenAIRE

    M. Athar; B. Ahmad

    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...

  8. 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. 

  9. A neuro-fuzzy approach for the diagnosis of depression

    Directory of Open Access Journals (Sweden)

    Subhagata Chattopadhyay

    2017-01-01

    Full Text Available Depression is considered to be a chronic mood disorder. This paper attempts to mathematically model how psychiatrists clinically perceive the symptoms and then diagnose depression states. According to Diagnostic and Statistical Manual (DSM-IV-TR, fourteen symptoms of adult depression have been considered. The load of each symptom and the corresponding severity of depression are measured by the psychiatrists (i.e. the domain experts. Using the Principal Component Analysis (PCA out of fourteen symptoms (as features seven has been extracted as latent factors. Using these features as inputs, a hybrid system consisting of Mamdani’s Fuzzy logic controller (FLC on a Feed Forward Multilayer Neural Net (FFMNN has been developed. The output of the hybrid system was tuned by a back propagation (BPNN algorithm. Finally, the model is validated using 302 real-world adult depression cases and 50 controls (i.e. normal population. The study concludes that the hybrid controller can diagnose and grade depression with an average accuracy of 95.50%. Finally, it is compared with the accuracies obtained by other techniques.

  10. 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.

  11. A novel approach to neuro-fuzzy classification.

    Science.gov (United States)

    Ghosh, Ashish; Shankar, B Uma; Meher, Saroj K

    2009-01-01

    A new model for neuro-fuzzy (NF) classification systems is proposed. The motivation is to utilize the feature-wise degree of belonging of patterns to all classes that are obtained through a fuzzification process. A fuzzification process generates a membership matrix having total number of elements equal to the product of the number of features and classes present in the data set. These matrix elements are the input to neural networks. The effectiveness of the proposed model is established with four benchmark data sets (completely labeled) and two remote sensing images (partially labeled). Different performance measures such as misclassification, classification accuracy and kappa index of agreement for completely labeled data sets, and beta index of homogeneity and Davies-Bouldin (DB) index of compactness for remotely sensed images are used for quantitative analysis of results. All these measures supported the superiority of the proposed NF classification model. The proposed model learns well even with a lower percentage of training data that makes the system fast.

  12. 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.

  13. 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.

  14. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

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

    2017-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Hamed Salmanzadeh

    2014-06-01

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

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

    Science.gov (United States)

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

    2012-09-01

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  18. 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.

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  20. 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.

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

    Science.gov (United States)

    Sutrisno; Widowati; Sunarsih; Kartono

    2018-01-01

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

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  3. 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.

  4. The Evaluation of Mineral Resources Development Efficiency Based on Hesitant Fuzzy Linguistic Approach and Modified TODIM

    OpenAIRE

    Li, Pu; Chen, Xudong; Qu, Xinyi; Xu, Qi

    2018-01-01

    The evaluation of mineral resources development efficiency is a typical multicriteria decision-making issue. Meanwhile, due to the limited existing technology, there might be subjectivity, ambiguity, and inaccuracy of the measurement of the evaluation index of mineral resources development efficiency. In this paper, we, considering the incomplete information, use the hesitant fuzzy linguistic approach to describe the psychological hesitation and ambiguity of the decision-maker in the actual e...

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

    OpenAIRE

    Zeynep Sener; Mehtap Dursun

    2014-01-01

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

  6. 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.

  7. Teachers’ recruitment process via MCDM methods: A case study in Bangladesh

    Directory of Open Access Journals (Sweden)

    C. L. Karmaker

    2015-08-01

    Full Text Available Evaluation of faculty members is very significant for educational organization to prompt reputation of the organization and to provide quality education. Teaching staff, the pillars of the educational institution, can change the whole nation stimulating the magnet of interest, knowledge, and wisdom in the pupils. Selecting a better academic staff among the others is very crucial for Human Resources Management (HRM as the success of any organization solely depends on how well it selects its manpower. Institute managing committee must have a reliable technique to judge a teachers’ ranking through multiple conflicting criteria because different teachers have various capabilities. In Bangladesh, it is a common practice in public engineering universities to select teachers only having good academic records. But teaching staff selection problem is a multi-staged decision-making problem having both quantitative and qualitative criteria. It is evident that it has become challenging as the number of alternatives and conflicting criteria increases. In this paper, a structured framework has been developed using MCDM methods both in fuzzy as well as non-fuzzy environments in the renowned engineering university of Bangladesh, where seven candidates under fifteen different sub-criteria are evaluated and ranked. The study helps the recruitment panel of educational organization in Bangladesh select the most eligible academic staff for required posts.

  8. 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.

  9. Multi Criteria Decision Making (MCDM). Complex problems made easy; Multi Criteria Decision Making (MCDM). Complexe vraagstukken behapbaar maken

    Energy Technology Data Exchange (ETDEWEB)

    Van Oeffelen, E.C.M.; Van Zundert, K.; Westerlaekn, A.C. [TNO, Delft (Netherlands)

    2011-12-15

    The existing housing stock needs to become smarter and more sustainable in its energy use. From a technical viewpoint, renovations can usually be realized successfully, but the multitude of preconditions such as phasing and the degree of inconvenience for residents often turn renovation into a complex matter. The MCDM method can be a suitable instrument in handling complex renovation issues. [Dutch] In de bestaande woningvoorraad moet slimmer en vooral duurzamer met energie worden omgegaan. Technisch gezien is een renovatie vaak goed realiseerbaar, maar vele randvoorwaarden, zoals fasering en mate van overlast voor bewoners, maken renovatievraagstukken vaak complex. De MCDM-methodiek kan een geschikt hulpmiddel zijn bij het aanpakken van complexe renovatievraagstukken.

  10. An Exhaustive Study of Possibility Measures of Interval-Valued Intuitionistic Fuzzy Sets and Application to Multicriteria Decision Making

    Directory of Open Access Journals (Sweden)

    Fatma Dammak

    2016-01-01

    Full Text Available This work is interested in showing the importance of possibility theory in multicriteria decision making (MCDM. Thus, we apply some possibility measures from literature to the MCDM method using interval-valued intuitionistic fuzzy sets (IVIFSs. These measures are applied to a decision matrix after being transformed with aggregation operators. The results are compared between each other and concluding remarks are drawn.

  11. A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach

    DEFF Research Database (Denmark)

    Govindan, Kannan; Khodaverdi, R.; Jafarian, A.

    2013-01-01

    . Traditionally, organizations consider criteria such as price, quality, flexibility, etc. when evaluating supplier performance. While the articles on the selection and evaluation of suppliers are abundant, those that consider sustainability issues are rather limited. This paper explores sustainable supply chain...... responsibility. Sustainable supply chain initiatives like supplier environmental and social collaboration can play a significant role in achieving the "triple bottom line" of social, environmental, and economic benefits. Supplier selection plays an important role in the management of a supply chain...... initiatives and examines the problem of identifying an effective model based on the Triple Bottom Line (TBL) approach (economic, environmental, and social aspects) for supplier selection operations in supply chains by presenting a fuzzy multi criteria approach. We use triangular fuzzy numbers to express...

  12. 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.

  13. On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach.

    Science.gov (United States)

    Baigzadehnoe, Barmak; Rahmani, Zahra; Khosravi, Alireza; Rezaie, Behrooz

    2017-09-01

    In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. 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

  15. 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 

  16. Fuzzy Saturated Output Feedback Tracking Control for Robot Manipulators: A Singular Perturbation Theory Based Approach

    Directory of Open Access Journals (Sweden)

    Huashan Liu

    2011-09-01

    Full Text Available To deal with the problem of the output feedback tracking (OFT control with bounded torque inputs of robot manipulators, we propose a generalized fuzzy saturated OFT controller based on singular perturbation theory. First, considering the fact that the output toque of joint actuators is limited, a general expression for a class of saturation functions is given to be applied in the control law. Second, to carry out the whole closed‐loop control with only position measurements, linear and nonlinear filters are optionally involved to generate a pseudo signal to surrogate the actual velocity tracking error. As a third contribution, a fuzzy regulator is added to obtain a self‐tuning performance in tackling the disturbances. Moreover, an explicit but strict stability proof of the system based on the stability theory of singularly perturbed systems is presented. Finally, numerical simulations on several sample controllers are implemented to verify the effectiveness of the proposed approach.

  17. Fuzzy Saturated Output Feedback Tracking Control for Robot Manipulators: A Singular Perturbation Theory Based Approach

    Directory of Open Access Journals (Sweden)

    Huashan Liu

    2011-09-01

    Full Text Available To deal with the problem of the output feedback tracking (OFT control with bounded torque inputs of robot manipulators, we propose a generalized fuzzy saturated OFT controller based on singular perturbation theory. First, considering the fact that the output toque of joint actuators is limited, a general expression for a class of saturation functions is given to be applied in the control law. Second, to carry out the whole closed-loop control with only position measurements, linear and nonlinear filters are optionally involved to generate a pseudo signal to surrogate the actual velocity tracking error. As a third contribution, a fuzzy regulator is added to obtain a self-tuning performance in tackling the disturbances. Moreover, an explicit but strict stability proof of the system based on the stability theory of singularly perturbed systems is presented. Finally, numerical simulations on several sample controllers are implemented to verify the effectiveness of the proposed approach.

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

    Science.gov (United States)

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

    2018-03-01

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

  19. A PSO-based approach to optimize the triangular membership functions in a fuzzy logic controller

    Science.gov (United States)

    Maniscalco, Vincenzo; Lombardo, Francesco

    2017-11-01

    In this paper a Particle Swarm Optimization (PSO) algorithm is considered in order to optimize the triangular Membership Functions (MF) in a Fuzzy Logic Controller (FLC). PSO algorithm belongs to the class of Swarm Intelligence (SI) techniques and is considered an efficient heuristic technique for optimization problem in a continuous and multidimen-sional search spaces. Performance of a FLC depends on the fuzzy partition of each input/output space considered and the PSO algorithm can be used to obtain the optimal or near optimal parameters of the triangular membership functions in order to achieve the best results in the defuzzification process. Simulation results obtained by this approach to tune the triangular membership functions of a FLC for an application concerning the optimization of the energy consumption in Industrial Wireless Sensor Networks (IWSN) are reported.

  20. Complexe vraagstukken behapbaar maken. Multi Criteria Decision Making (MCDM)

    NARCIS (Netherlands)

    Oeffelen, E.C.M. van; Westerlaken, A.C.; Zundert, K. van

    2011-01-01

    In de bestaande woningbouwvoorraad moet slimmer en vooral duurzamer met energie worden omgegaan. Technisch gezien is een renovatie vaak goed realiseerbaar, maar vele randvoorwaarden, zoals fasering en mate van overlast voor bewoners, maken renovatievraagstukken vaak comlex. De MCDM-methodiek kan een

  1. 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.

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

    Indian Academy of Sciences (India)

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

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

    Indian Academy of Sciences (India)

    Abstract. 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.

  4. Water level forecasting through fuzzy logic and artificial neural network approaches

    Directory of Open Access Journals (Sweden)

    S. Alvisi

    2006-01-01

    Full Text Available In this study three data-driven water level forecasting models are presented and discussed. One is based on the artificial neural networks approach, while the other two are based on the Mamdani and the Takagi-Sugeno fuzzy logic approaches, respectively. All of them are parameterised with reference to flood events alone, where water levels are higher than a selected threshold. The analysis of the three models is performed by using the same input and output variables. However, in order to evaluate their capability to deal with different levels of information, two different input sets are considered. The former is characterized by significant spatial and time aggregated rainfall information, while the latter considers rainfall information more distributed in space and time. The analysis is made with great attention to the reliability and accuracy of each model, with reference to the Reno river at Casalecchio di Reno (Bologna, Italy. It is shown that the two models based on the fuzzy logic approaches perform better when the physical phenomena considered are synthesised by both a limited number of variables and IF-THEN logic statements, while the ANN approach increases its performance when more detailed information is used. As regards the reliability aspect, it is shown that the models based on the fuzzy logic approaches may fail unexpectedly to forecast the water levels, in the sense that in the testing phase, some input combinations are not recognised by the rule system and thus no forecasting is performed. This problem does not occur in the ANN approach.

  5. Application of an Integrated Model with MCDM and IPA to Evaluate the Service Quality of Transshipment Port

    Directory of Open Access Journals (Sweden)

    Chien-Chang Chou

    2013-01-01

    Full Text Available It is often to solve complex decision-making problems in the marine transportation environment, such as the evaluation of service quality and the location choice of ports. In this paper, an integrated model with multiple-criteria decision making (MCDM and importance-performance analysis (IPA is presented and then is applied to solve the problem of service quality evaluation of transshipment port. The MCDM approach can be used to deal with both quantitative data and qualitative ratings simultaneously. The IPA approach can be applied to realize the shortcomings of service quality of ports and rank the ranking of strategies for improving service quality of transshipment port. Finally, some useful suggestions for improving the service quality of ports are given in the paper.

  6. Probabilistic Fuzzy Approach to Evaluation of Logistics Service Effectiveness

    OpenAIRE

    Rudnik Katarzyna; Pisz Iwona

    2014-01-01

    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 ext...

  7. 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.

  8. 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.

  9. Groundwater Exploration Using Fuzzy Logic Approach in GIS for AN Area around AN Anticline, Fars Province

    Science.gov (United States)

    Rafati, S.; Nikeghbal, M.

    2017-09-01

    In the recent years, the over-use of water resource due to the population growth and industrial developing has become serious. With attention to demand for water, it's essential to explore and evaluate new water resource and mapping its potential. In this paper, a fuzzy set theory, as a knowledge driven approach for map combination, was applied to produce a potential map for ground water resources. To achieve this objective, a variety of spatial data including geology, slope, elevation, drainage, fault and joint were complied. Then fuzzy membership functions were evaluated for each data layer. These data were integrated using the fuzzy γ operator with a value of γ = 0.95. The final map indicates Quaternary formation consists of alluvial deposits near the 200 meter distance from the anti-cline as a suitable area for groundwater resource. Finding out an accurate method which accelerates processing for determining the location of groundwater before drilling is an effective solution leading to save budget and time.

  10. A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control.

    Science.gov (United States)

    Ajiboye, Abidemi Bolu; Weir, Richard F ff

    2005-09-01

    This paper presents a heuristic fuzzy logic approach to multiple electromyogram (EMG) pattern recognition for multifunctional prosthesis control. Basic signal statistics (mean and standard deviation) are used for membership function construction, and fuzzy c-means (FCMs) data clustering is used to automate the construction of a simple amplitude-driven inference rule base. The result is a system that is transparent to, and easily "tweaked" by, the prosthetist/clinician. Other algorithms in current literature assume a longer period of unperceivable delay, while the system we present has an update rate of 45.7 ms with little postprocessing time, making it suitable for real-time application. Five subjects were investigated (three with intact limbs, one with a unilateral transradial amputation, and one with a unilateral transradial limb-deficiency from birth). Four subjects were used for system offline analysis, and the remaining intact-limbed subject was used for system real-time analysis. We discriminated between four EMG patterns for subjects with intact limbs, and between three patterns for limb-deficient subjects. Overall classification rates ranged from 94% to 99%. The fuzzy algorithm also demonstrated success in real-time classification, both during steady state motions and motion state transitioning. This functionality allows for seamless control of multiple degrees-of-freedom in a multifunctional prosthesis.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    2016-02-01

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

  13. An effective fuzzy kernel clustering analysis approach for gene expression data.

    Science.gov (United States)

    Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

    2015-01-01

    Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

  14. A Fuzzy Rule-Based Penalty Function Approach for Constrained Evolutionary Optimization.

    Science.gov (United States)

    Saha, Chiranjib; Das, Swagatam; Pal, Kunal; Mukherjee, Satrajit

    2016-12-01

    This paper proposes a novel fuzzy rule-based penalty function approach for solving single-objective nonlinearly constrained optimization problems. Of all the existing state-of-the-art constraint handling techniques, the conventional method of penalty can be easily implemented because of its simplicity but suffers from the lack of robustness. To mitigate the problem of parameter dependency, several forms of adaptive penalties have been suggested in literature. Instead of identifying a complex mathematical function to compute the penalty for constraint violation, we propose a Mamdani type IF-THEN rule-based fuzzy inference system that incorporates all the required criteria of self-adaptive penalty without formulating an explicit mapping. Effectiveness of the proposed constrained optimization algorithm has been empirically validated on the basis of the standard optimality theorems from the literature on mathematical programming. Simulation results show that fuzzy penalty not only surpasses its existing counterpart i.e., self adaptive penalty, but also remain competitive against several other standard as well as currently developed complex constraint handling strategies.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Vahid Reza Salamat

    2018-09-01

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

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

    Directory of Open Access Journals (Sweden)

    m. s. osman

    2017-09-01

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

  18. Selecting Green Supplier of Thermal Power Equipment by Using a Hybrid MCDM Method for Sustainability

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2014-01-01

    Full Text Available With the growing worldwide awareness of environmental protection and sustainable development, green purchasing has become an important issue for companies to gain environmental and developmental sustainability. Thermal power is the main power generation form in China, and the green supplier selection is essential to the smooth and sustainable construction of thermal power plants. Therefore, selecting the proper green supplier of thermal power equipment is very important to the company’s sustainable development and the sustainability of China’s electric power industry. In this paper, a hybrid fuzzy multi-attribute decision making approach (fuzzy entropy-TOPSIS is proposed for selecting the best green supplier. The fuzzy set theory is applied to translate the linguistic preferences into triangular fuzzy numbers. The subjective criteria weights are determined by using decision makers’ superiority linguistic ratings and the objective ones are determined by combining the superiority linguistic ratings and fuzzy-entropy weighting method. The fuzzy TOPSIS is employed to generate an overall performance score for each green supplier. An empirical green supplier selection is conducted to illustrate the effectiveness of this proposed fuzzy entropy-TOPSIS approach. This proposed fuzzy entropy-TOPSIS approach can select the proper green supplier of thermal power equipment, which contributes to promoting the company’s sustainable development and the sustainability of China’s electric power industry to some extent.

  19. Early software reliability prediction a fuzzy logic approach

    CERN Document Server

    Pandey, Ajeet Kumar

    2013-01-01

    The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An important approach presented in this book is a model to classify the modules into two categories (a) fault-prone and (b) not fault-prone. The methods presented in this book for assessing expected number of faults present in the software, assessing expected number of faults present at the end of each phase and classification...

  20. Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2016-04-01

    Full Text Available Optimal siting of electric vehicle charging stations (EVCSs is crucial to the sustainable development of electric vehicle systems. Considering the defects of previous heuristic optimization models in tackling subjective factors, this paper employs a multi-criteria decision-making (MCDM framework to address the issue of EVCS siting. The initial criteria for optimal EVCS siting are selected from extended sustainability theory, and the vital sub-criteria are further determined by using a fuzzy Delphi method (FDM, which consists of four pillars: economy, society, environment and technology perspectives. To tolerate vagueness and ambiguity of subjective factors and human judgment, a fuzzy Grey relation analysis (GRA-VIKOR method is employed to determine the optimal EVCS site, which also improves the conventional aggregating function of fuzzy Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR. Moreover, to integrate the subjective opinions as well as objective information, experts’ ratings and Shannon entropy method are employed to determine combination weights. Then, the applicability of proposed framework is demonstrated by an empirical study of five EVCS site alternatives in Tianjin. The results show that A3 is selected as the optimal site for EVCS, and sub-criteria affiliated with environment obtain much more attentions than that of other sub-criteria. Moreover, sensitivity analysis indicates the selection results remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of proposed model and evaluation results. This study provides a comprehensive and effective method for optimal siting of EVCS and also innovates the weights determination and distance calculation for conventional fuzzy VIKOR.

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

    International Nuclear Information System (INIS)

    Feng Gang; Chen Guanrong

    2005-01-01

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

  2. 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.

  3. PRESENTING SEARCH RESULT WITH REDUCED UNWANTED WEB ADDRESSES USING FUZZY BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Nancy Jasmine Goldena

    2017-07-01

    Full Text Available Big Data is now the most talked about research subject. Over the year with the internet and storage space expansions vast swaths of data are available for would be searcher. About a decade ago when a content was searched, due to minimum amount of content often you end up with accurate set of results. But nowadays most of the data, if not all are sometimes vague and not even sometime pertain to area of search it was indented to. Hence here a novel approach is presented to perform data cleaning using a simple but effective fuzzy rule to weed out data that won’t produce accurate data.

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

    Science.gov (United States)

    Huang, Sheng-Juan; Yang, Guang-Hong

    2017-09-01

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

  5. 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.

  6. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method.

    Science.gov (United States)

    Alguliyev, Rasim M; Aliguliyev, Ramiz M; Mahmudova, Rasmiyya S

    2015-01-01

    Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  7. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2015-01-01

    Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  8. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Science.gov (United States)

    Alguliyev, Rasim M.; Aliguliyev, Ramiz M.; Mahmudova, Rasmiyya S.

    2015-01-01

    Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method. PMID:26516634

  9. Applying a Hybrid MCDM Model for Six Sigma Project Selection

    Directory of Open Access Journals (Sweden)

    Fu-Kwun Wang

    2014-01-01

    Full Text Available Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS is a type of multiple criteria decision making (MCDM problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL technique, analytic network process (ANP, and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

  10. Genetic algorithm based hybrid approach to solve fuzzy multi-objective assignment problem using exponential membership function.

    Science.gov (United States)

    Dhodiya, Jayesh M; Tailor, Anita Ravi

    2016-01-01

    This paper presents a genetic algorithm based hybrid approach for solving a fuzzy multi-objective assignment problem (FMOAP) by using an exponential membership function in which the coefficient of the objective function is described by a triangular possibility distribution. Moreover, in this study, fuzzy judgment was classified using α -level sets for the decision maker (DM) to simultaneously optimize the optimistic, most likely, and pessimistic scenarios of fuzzy objective functions. To demonstrate the effectiveness of the proposed approach, a numerical example is provided with a data set from a realistic situation. This paper concludes that the developed hybrid approach can manage FMOAP efficiently and effectively with an effective output to enable the DM to take a decision.

  11. Efficient Approach for RLS Type Learning in TSK Neural Fuzzy Systems.

    Science.gov (United States)

    Yeh, Jen-Wei; Su, Shun-Feng

    2017-09-01

    This paper presents an efficient approach for the use of recursive least square (RLS) learning algorithm in Takagi-Sugeno-Kang neural fuzzy systems. In the use of RLS, reduced covariance matrix, of which the off-diagonal blocks defining the correlation between rules are set to zeros, may be employed to reduce computational burden. However, as reported in the literature, the performance of such an approach is slightly worse than that of using the full covariance matrix. In this paper, we proposed a so-called enhanced local learning concept in which a threshold is considered to stop learning for those less fired rules. It can be found from our experiments that the proposed approach can have better performances than that of using the full covariance matrix. Enhanced local learning method can be more active on the structure learning phase. Thus, the method not only can stop the update for insufficiently fired rules to reduce disturbances in self-constructing neural fuzzy inference network but also raises the learning speed on structure learning phase by using a large backpropagation learning constant.

  12. 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.

  13. 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.

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

    Science.gov (United States)

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

    2017-11-01

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

  15. 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.

  16. 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.

  17. An Exploratory Analysis for the Selection and Implementation of Advanced Manufacturing Technology by Fuzzy Multi-criteria Decision Making Methods: A Comparative Study

    Science.gov (United States)

    Nath, Surajit; Sarkar, Bijan

    2017-08-01

    Advanced Manufacturing Technologies (AMTs) offer opportunities for the manufacturing organizations to excel their competitiveness and in turn their effectiveness in manufacturing. Proper selection and evaluation of AMTs is the most significant task in today's modern world. But this involves a lot of uncertainty and vagueness as it requires many conflicting criteria to deal with. So the task of selection and evaluation of AMTs becomes very tedious for the evaluators as they are not able to provide crisp data for the criteria. Different Fuzzy Multi-criteria Decision Making (MCDM) methods help greatly in dealing with this problem. This paper focuses on the application of two very much potential Fuzzy MCDM methods namely COPRAS-G, EVAMIX and a comparative study between them on some rarely mentioned criteria. Each of the two methods is very powerful evaluation tool and has beauty in its own. Although, performance wise these two methods are almost at same level, but, the approach of each one of them are quite unique. This uniqueness is revealed by introducing a numerical example of selection of AMT.

  18. A study on the ranking performance of some MCDM methods for industrial robot selection problems

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2016-06-01

    Full Text Available In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM methods, i.e. weighted sum method (WSM, weighted product method (WPM, weighted aggregated sum product assessment (WASPAS method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA method, and multiplicative form of MOORA method (MULTIMOORA is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.

  19. 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

    2013-01-01

    Today's international business environment has forced many firms to focus on supply chain management to gain a competitive advantage. During recent years, supplier selection process in the supply chain has become a key strategic consideration. With the growing worldwide awareness of environmental...... 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...... is presented to demonstrate the effectiveness of the proposed approach....

  20. The Implementation of an MCDM Tool for the Acquisition of Military Equipment

    Science.gov (United States)

    2009-10-01

    RTO-MP-SAS-080 17 - 1 The Implementation of an MCDM Tool for the Acquisition of Military Equipment Frédéric Hallot, Philippe De Beir, Hugo...our experience as well in teaching as in consultancy at the Royal Military Academy we learned that previously existing MCDM software did not fit well...AND SUBTITLE The Implementation of an MCDM Tool for the Acquisition of Military Equipment 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

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

    Indian Academy of Sciences (India)

    ... 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.

  2. 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.

  3. Development of a framework for resilience measurement: Suggestion of fuzzy Resilience Grade (RG) and fuzzy Resilience Early Warning Grade (REWG).

    Science.gov (United States)

    Omidvar, Mohsen; Mazloumi, Adel; Mohammad Fam, Iraj; Nirumand, Fereshteh

    2017-01-01

    Resilience engineering (RE) can be an alternative technique to the traditional risk assessment and management techniques, to predict and manage safety conditions of modern socio-technical organizations. While traditional risk management approaches are retrospective and highlight error calculation and computation of malfunction possibilities, resilience engineering seeks ways to improve capacity at all levels of organizations in order to build strong yet flexible processes. Considering the resilience potential measurement as a concern in complex working systems, the aim of this study was to quantify the resilience by the help of fuzzy sets and Multi-Criteria Decision-Making (MCDM) techniques. In this paper, we adopted the fuzzy analytic hierarchy process (FAHP) method to measure resilience in a gas refinery plant. A resilience assessment framework containing six indicators, each with its own sub-indicators, was constructed. Then, the fuzzy weights of the indicators and the sub-indicators were derived from pair-wise comparisons conducted by experts. The fuzzy evaluating vectors of the indicators and the sub-indicators computed according to the initial assessment data. Finally, the Comprehensive Resilience Index (CoRI), Resilience Grade (RG), and Resilience Early Warning Grade (REWG) were established. To demonstrate the applicability of the proposed method, an illustrative example in a gas refinery complex (an instance of socio-technical systems) was provided. CoRI of the refinery ranked as "III". In addition, for the six main indicators, RG and REWG ranked as "III" and "NEWZ", respectively, except for C3, in which RG ranked as "II", and REWG ranked as "OEWZ". The results revealed the engineering practicability and usefulness of the proposed method in resilience evaluation of socio-technical systems.

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

    Directory of Open Access Journals (Sweden)

    L. C. Félix-Herrán

    2015-01-01

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

  5. 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%.

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

    Science.gov (United States)

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

    2018-03-01

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

  7. 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.

  8. An Extended Step-Wise Weight Assessment Ratio Analysis with Symmetric Interval Type-2 Fuzzy Sets for Determining the Subjective Weights of Criteria in Multi-Criteria Decision-Making Problems

    Directory of Open Access Journals (Sweden)

    Mehdi Keshavarz-Ghorabaee

    2018-03-01

    Full Text Available Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM. Step-wise Weight Assessment Ratio Analysis (SWARA is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.

  9. A fuzzy locally adaptive Bayesian segmentation approach for volume determination in PET

    Science.gov (United States)

    Hatt, Mathieu; Cheze-Lerest, Catherine; Turzo, Alexandre; Roux, Christian; Visvikis, Dimitris

    2009-01-01

    Accurate volume estimation in PET is crucial for different oncology applications. The objective of our study was to develop a new fuzzy locally adaptive Bayesian (FLAB) segmentation for automatic lesion volume delineation. FLAB was compared with a threshold approach as well as the previously proposed fuzzy hidden Markov chains (FHMC) and the Fuzzy C-Means (FCM) algorithms. The performance of the algorithms was assessed on acquired datasets of the IEC phantom, covering a range of spherical lesion sizes (10–37mm), contrast ratios (4:1 and 8:1), noise levels (1, 2 and 5 min acquisitions) and voxel sizes (8mm3 and 64mm3). In addition, the performance of the FLAB model was assessed on realistic non-uniform and non-spherical volumes simulated from patient lesions. Results show that FLAB performs better than the other methodologies, particularly for smaller objects. The volume error was 5%–15% for the different sphere sizes (down to 13mm), contrast and image qualities considered, with a high reproducibility (variation <4%). By comparison, the thresholding results were greatly dependent on image contrast and noise, whereas FCM results were less dependent on noise but consistently failed to segment lesions <2cm. In addition, FLAB performed consistently better for lesions <2cm in comparison to the FHMC algorithm. Finally the FLAB model provided errors less than 10% for non-spherical lesions with inhomogeneous activity distributions. Future developments will concentrate on an extension of FLAB in order to allow the segmentation of separate activity distribution regions within the same functional volume as well as a robustness study with respect to different scanners and reconstruction algorithms. PMID:19150782

  10. Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach.

    Science.gov (United States)

    Huo, Hongyuan; Guo, Jifa; Li, Zhao-Liang

    2018-01-26

    Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

  11. Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach

    Directory of Open Access Journals (Sweden)

    Hongyuan Huo

    2018-01-01

    Full Text Available Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM* approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

  12. Clustering by fuzzy neural gas and evaluation of fuzzy clusters.

    Science.gov (United States)

    Geweniger, Tina; Fischer, Lydia; Kaden, Marika; Lange, Mandy; Villmann, Thomas

    2013-01-01

    We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.

  13. Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters

    OpenAIRE

    Geweniger, Tina; Fischer, Lydia; Kaden, Marika; Lange, Mandy; Villmann, Thomas

    2013-01-01

    We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.

  14. AN APPROACH TO REMOVE THE EFFECT OF RANDOM INITIALIZATION FROM FUZZY C-MEANS CLUSTERING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    Samarjit Das

    2014-01-01

    Full Text Available Out of the different available fuzzy clustering techniques Bezdek’s Fuzzy C-Means clustering technique is among the most popular ones. Due to the random initialization of the membership values the performance of Fuzzy C-Means clustering technique varies significantly in its different executions. We have tried to remove the effect of random initialization from Fuzzy CMeans clustering technique by using the Subtractive clustering technique of Chiu as a preprocessor to it. We have also provided a comparison of the performance of our method with those of Fuzzy C-Means clustering technique and Subtractive clustering technique.

  15. Hybrid Fuzzy-Genetic Approach Integrating Peak Identification and Spectrum Fitting for Complex Gamma-Ray Spectra Analysis

    Science.gov (United States)

    Alamaniotis, Miltiadis; Jevremovic, Tatjana

    2015-06-01

    A novel hybrid approach for analysis of complex gamma-ray spectra of various origins is described and the test results using spectra obtained from a sodium iodide detector (NaI) are presented. This novel approach exploits the synergism of two artificial intelligence tools; fuzzy logic and genetic algorithms, where the two are merged to identify isotopes and their respective contribution in a given spectrum. The fuzzy logic module focuses on identifying isotopes in the spectrum, while the genetic algorithm (GA) fits and subsequently computes the fractional abundances of the identified isotopes. The fitting of the spectrum is controlled by an assessment procedure based on the test for significance of abundance coefficients, and on the computation of Theil coefficients. This unique synergism between fuzzy logic and GA presents a novel mechanism for automated selection of isotopes for use in spectrum fitting, and as a result eliminates manually-based fitting and/or user intervention. A variety of test cases-including NaI real measured spectra-are used to benchmark this new approach. In addition, the performance of the hybrid method is compared to the multiple linear regression (MLR) fitting approach, along with the combination of fuzzy logic with MLR. This comparison demonstrates a slight superiority of this novel approach regarding accuracy, precision and number of reported false detections.

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

    Science.gov (United States)

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

    2015-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Giovanni Pau

    2018-02-01

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

  18. Novel approach to control false positive rate in fuzzy cluster analysis of fMRI

    Science.gov (United States)

    Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

    2004-04-01

    Fuzzy c-means (FCM) suffers from some limitations such as the need for a priori knowledge of the number of clusters, and unknown statistical significance and instability of the results, when it is applied to the raw fMRI time series. Based on randomization, we developed a method to control the false positive detection rate in FCM and estimate the statistical significance of the results. Using this novel approach, we proposed an fMRI activation detection method which uses FCM with controlled false positive rate. The ability of the method in controlling the false positive rate is shown by an analysis of false positives in activation maps of resting-state fMRI data. Controlling the false positive rate allows comparison of different feature spaces and fuzzy clustering methods. A new feature space, in multi and scalar wavelet domain, is proposed for activation detection in fMRI to address the stability problem. Finally, using the proposed method for controlling the false positive rate, the proposed feature space is compared to the cross-correlation feature space.

  19. Selective mining of multiple-layer lignite deposits. A fuzzy approach

    Energy Technology Data Exchange (ETDEWEB)

    Galetakis, M.; Vasiliou, A. [Technical University of Crete, Khania (Greece). Dept. of Mineral Resources Engineering

    2010-06-15

    In this paper the development and the application of a fuzzy expert system for the evaluation of the exploitable reserves of multiple-layer lignite deposits, mined by continuous surface methods, is presented. The exploitable reserves are determined decisively by the structure of these deposits, as well as by the limitations of the used mining systems. In practice, thin layers of lignite and interbedded waste layers are grouped under specified assumptions regarding thickness and ash content, to form the exploitable blocks. Moreover, the decision for excavating such a block is made under subjective constraints of different importance, or by using uncertain data. Advances in fuzzy inference systems (FIS) have provided a new approach to the evaluation of multiple-layer lignite deposits. FIS have the ability to handle imprecise, incomplete or linguistically ambiguous information and incorporate them into decision-making processes. In the developed FIS (Mamdani type) new linguistic variables, related to working conditions, operators' experience and production were involved. The FIS was used for the estimation of the exploitable reserves of the Southern Field lignite deposit, located in the area of Ptolemais (Greece).

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

    Science.gov (United States)

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

    2011-02-01

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

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

    Science.gov (United States)

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

    2017-05-01

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

  2. 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.

  3. 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.

  4. A novel generic hebbian ordering-based fuzzy rule base reduction approach to mamdani neuro-fuzzy system.

    Science.gov (United States)

    Liu, Feng; Quek, Chai; Ng, Geok See

    2007-06-01

    There are two important issues in neuro-fuzzy modeling: (1) interpretability--the ability to describe the behavior of the system in an interpretable way--and (2) accuracy--the ability to approximate the outcome of the system accurately. As these two objectives usually exert contradictory requirements on the neuro-fuzzy model, certain compromise has to be undertaken. This letter proposes a novel rule reduction algorithm, namely, Hebb rule reduction, and an iterative tuning process to balance interpretability and accuracy. The Hebb rule reduction algorithm uses Hebbian ordering, which represents the degree of coverage of the samples by the rule, as an importance measure of each rule to merge the membership functions and hence reduces the number of the rules. Similar membership functions (MFs) are merged by a specified similarity measure in an order of Hebbian importance, and the resultant equivalent rules are deleted from the rule base. The rule with a higher Hebbian importance will be retained among a set of rules. The MFs are tuned through the least mean square (LMS) algorithm to reduce the modeling error. The tuning of the MFs and the reduction of the rules proceed iteratively to achieve a balance between interpretability and accuracy. Three published data sets by Nakanishi (Nakanishi, Turksen, & Sugeno, 1993), the Pat synthetic data set (Pal, Mitra, & Mitra, 2003), and the traffic flow density prediction data set are used as benchmarks to demonstrate the effectiveness of the proposed method. Good interpretability, as well as high modeling accuracy, are derivable simultaneously and are suitably benchmarked against other well-established neuro-fuzzy models.

  5. 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.

  6. A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection

    Directory of Open Access Journals (Sweden)

    Bowen Wang

    2014-01-01

    Full Text Available 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. 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.

  8. A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection

    Science.gov (United States)

    Wang, Bowen; 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. PMID:25215319

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

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    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. Fuzzy Analytical Hierarchy Process for Ecological Risk Assessment

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    Radionovs Andrejs

    2016-12-01

    Full Text Available Being able to evaluate risks is an important task in many areas of human activity: economics, ecology, etc. Usually, environmental risk assessment is carried out on the basis of multiple and sometimes conflicting factors. Using multiple criteria decision-making (MCDM methodology is one of the possible ways to solve the problem. Analytic hierarchy process (AHP is one of the most commonly used MCDM methods, which combines subjective and personal preferences in the risk assessment process. However, the AHP involves human subjectivity, which introduces vagueness type of uncertainty and requires the use of decision making under those uncertainties. In this paper, work with uncertainty is considered using fuzzy-based techniques. The paper also analyses the ecological risk assessment towards human health in case of gaseous substance escape at a chemical factory using the fuzzy analytical hierarchy process.

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

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    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.

  12. Prediction of contact forces of underactuated finger by adaptive neuro fuzzy approach

    Science.gov (United States)

    Petković, Dalibor; Shamshirband, Shahaboddin; Abbasi, Almas; Kiani, Kourosh; Al-Shammari, Eiman Tamah

    2015-12-01

    To obtain adaptive finger passive underactuation can be used. Underactuation principle can be used to adapt shapes of the fingers for grasping objects. The fingers with underactuation do not require control algorithm. In this study a kinetostatic model of the underactuated finger mechanism was analyzed. The underactuation is achieved by adding the compliance in every finger joint. Since the contact forces of the finger depend on contact position of the finger and object, it is suitable to make a prediction model for the contact forces in function of contact positions of the finger and grasping objects. In this study prediction of the contact forces was established by a soft computing approach. Adaptive neuro-fuzzy inference system (ANFIS) was applied as the soft computing method to perform the prediction of the finger contact forces.

  13. 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.

  14. 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

  15. 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.

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

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

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

  17. Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

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    S. Ebrahimnejad

    2012-04-01

    Full Text Available The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.

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

    OpenAIRE

    Xiong, Guojiang; Shi, Dongyuan; Zhu, Lin; Duan, Xianzhong

    2013-01-01

    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 conclusi...

  19. Modeling and optimization of ultrasonic metal welding on dissimilar sheets using fuzzy based genetic algorithm approach

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    Mantra Prasad Satpathy

    2015-12-01

    Full Text Available Ultrasonic welding has been used in the market over the past twenty years and serving to the manufacturing industries like aviation, medical, microelectronics and many more due to various hurdles faced by conventional fusion welding process. It takes very short time (less than one second to weld materials, thus it can be used for mass production. But many times, the problems faced by industries due to this process are the poor weld quality and strength of the joints. In fact, the quality and success of the welding depend upon its control parameters. In this present study, the control parameters like vibration amplitude, weld pressure and weld time are considered for the welding of dissimilar metals like aluminum (AA1100 and brass (UNS C27000 sheet of 0.3 mm thickness. Experiments are conducted according to the full factorial design with four replications to obtain the responses like tensile shear stress, T-peel stress and weld area. All these data are utilized to develop a non-linear second order regression model between the responses and predictors. As the quality is an important issue in these manufacturing industries, the optimal combinations of these process parameters are found out by using fuzzy logic approach and genetic algorithm (GA approach. During experiments, the temperature measurement of the weld zone has also been performed to study its effect on different quality characteristics. From the confirmatory test, it has been observed that, the fuzzy logic yields better output results than GA. A variety of weld quality levels, such as “under weld”, “good weld” and “over weld” have also been defined by performing micro structural analysis.

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

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    Igor V. KONONENKO

    2017-03-01

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

  1. 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.

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

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    Abdullah M. Iliyasu

    2017-12-01

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

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

    Science.gov (United States)

    Iliyasu, Abdullah M; Fatichah, Chastine

    2017-12-19

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

  4. LANDFILL SITTING USING MCDM in TEHRAN METROPOLITAN

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    Bahram Abediniangerabi

    2016-01-01

    Full Text Available Managing Municipal Solid Waste in order to control waste materials in Tehran Metropolitan with a population of over 8.5 million persons and daily production of 7500 tons of trash seems an evitable necessity. Daily production of such amount of trash and accumulation of them in the southern part of Tehran (Kahrizak due to lack of proper and standard methods of landfilling have caused severe problems by creating a latex lake of twelve hectares. Among these problems, penetration of infection and contamination to underground waters, causing excessive problems for soil and agricultural lands can be mentioned. In such conditions caused for Tehran, lack of solution finding for the issue would bring heavy outcomes for the Tehran Metropolitan in terms of environmental and economic issues. In this paper, efforts are taken to find a new place as a landfill by applying sustainable development approach. For this, in order to use the criteria propounded in sustainable development, multi-criteria decision making methods has been applied for weighing and spatial analysis has been used to combining them for indicating the most appropriate site. In this way, the new site would be selected by observance of sustainable development would be a place with the least environmental and social damages while being economically affordable.

  5. 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.

  6. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method.

    Science.gov (United States)

    Liu, Hu-Chen; Wu, Jing; Li, Ping

    2013-12-01

    Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include "incineration", "steam sterilization", "microwave" and "landfill". The results obtained using the proposed approach are analyzed in a comparative way. Copyright © 2013. Published by Elsevier Ltd.

  7. Agility assessment using fuzzy logic approach: a case of healthcare dispensary.

    Science.gov (United States)

    Suresh, M; Patri, Rojalin

    2017-06-09

    Agile concepts are not only beneficial for manufacturing sector but also for service sector such as healthcare. However, assessment of agility has been predominantly done in manufacturing enterprises. This study demonstrates a means to measure agility of a healthcare organization by assessing agility of a university dispensary. Its contribution to the knowledge base is twofold. First, it proposes a means to measure the agility of a healthcare organization and second, it identifies the attributes that prevent agile performance and outlines the suggestive measure to enhance its agile capabilities. A case study approach has been adopted and fuzzy logic has been employed to measure the agility of the case dispensary. At first, the measures of assessment which include four enablers, fifteen criteria and forty-five attributes have been identified from the literature and rated by the experts indicating the importance of the measures in the assessment. Then, the case dispensary has been assessed on those measures by collecting observed performance rating from decision makers. At last, Fuzzy logic has been applied on the performance rating data to analyze and interpret the agile capability of the dispensary. The findings suggest that transparent information flow, adequate salary and bonuses for caregivers, reading error in medical descriptions, in house/nearby pathology laboratory services, technical up-gradation of dispensary equipments and facilities, minimization of patient throughput time and adequate training programme for safety practices are the attributes that weakens agile capability of the University dispensary. The current agility of the dispensary was found to be 'Agile' which is average in relation to the agility labels. Attributes such as transparent information flow, adequate salary and bonuses for caregivers, elimination of reading error in medical descriptions, in house/nearby pathology laboratory services, technical up-gradation of dispensary equipments

  8. A Hybrid MCDM Model for New Product Development: Applied on the Taiwanese LiFePO4 Industry

    Directory of Open Access Journals (Sweden)

    Wen-Chin Chen

    2015-01-01

    Full Text Available Recent years, since problems with respect to atmosphere pollution hasten countries to accentuate green-related policy regarding the sustainable energy, the lithium-iron phosphate (LiFePO4 battery has been appealed to the world. However, more and more firms invest the LiFePO4 batteries production that has launched a fierce competition. Successful new product development (NPD processes have been considered the key for LiFePO4 battery firms to increase their competitive advantage. Firms must make correct decision faster due to the rapid development of technology and the decreasing product life cycle. This study proposes a hybrid multiple criteria decision making (MCDM model based on the literature review and consultation with the experts, interpretive structural modeling (ISM, and fuzzy analytic network process (FANP for evaluating various strategies for NPD. First of all, reviewing of literature and meeting with the experts are used to screen factors and select the criteria. Then, an ISM is managed to determine the feedback and interdependency of those factors in a network. Finally, a fuzzy theory is applied to resolve the linguistic hedges and an ANP is adopted to obtain the weights of all the factors. A case study is undertaken to validate the model in a Taiwanese company that provides professional packing and design for lithium-iron phosphate battery.

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

    Directory of Open Access Journals (Sweden)

    Faiz Muhammad Khan

    2014-01-01

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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Breno Pinheiro Jacob

    2008-06-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  14. A New Perspective on Formation of Haze-Fog: The Fuzzy Cognitive Map and Its Approaches to Data Mining

    Directory of Open Access Journals (Sweden)

    Zhen Peng

    2017-02-01

    Full Text Available Haze-fog has seriously hindered the sustainable development of the ecological environment and caused great harm to the physical and mental health of residents in China. Therefore, it is important to probe the formation of haze-fog for its early warning and prevention. The formation of haze-fog is, in fact, a fuzzy nonlinear process. The formation of haze-fog is such a complex process that it is difficult to simulate its dynamic evolution using traditional methods, mainly because of the lack of their consideration of the nonlinear relationships. It is, therefore, essential to explore new perspectives on the formation of haze-fog. In this work, previous research on haze-fog formation is summarized first. Second, a new perspective is proposed on the application of fuzzy cognitive map to the formation of haze-fog. Third, a data mining method based on the genetic algorithm is used to discover the causality values of a fuzzy cognitive map (FCM for hazefog formation. Finally, simulation results are obtained through an experiment using the fuzzy cognitive map and its data mining method for the formation of haze-fog. The validity of this approach is determined by definition of a simple rule and the Kappa values. Thus, this research not only provides a new idea using FCM modeling the formation of haze-fog, but also uses an effective method of FCM for solving the nonlinear dynamics of the haze-fog formation.

  15. 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

  16. 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.

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

    International Nuclear Information System (INIS)

    Lee, S.

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Azadeh Hashemian

    2008-06-01

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

  19. 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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Chong Jeffrey Hong Seng

    2018-01-01

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

  2. 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. .

  3. Fuzzy Bases of Fuzzy Domains

    Directory of Open Access Journals (Sweden)

    Sanping Rao

    2013-01-01

    Full Text Available This paper is an attempt to develop quantitative domain theory over frames. Firstly, we propose the notion of a fuzzy basis, and several equivalent characterizations of fuzzy bases are obtained. Furthermore, the concept of a fuzzy algebraic domain is introduced, and a relationship between fuzzy algebraic domains and fuzzy domains is discussed from the viewpoint of fuzzy basis. We finally give an application of fuzzy bases, where the image of a fuzzy domain can be preserved under some special kinds of fuzzy Galois connections.

  4. Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method

    Science.gov (United States)

    Madić, Miloš; Radovanović, Miroslav; Petković, Dušan; Nedić, Bogdan

    2015-07-01

    Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.

  5. Enhancement of SAR images using fuzzy shrinkage technique in ...

    Indian Academy of Sciences (India)

    Shivakumara Swamy Puranik Math

    2017-08-03

    Aug 3, 2017 ... fuzzy techniques, such as fuzzy clustering, fuzzy rule-based approach, and fuzzy integration approach. In the proposed work, the fuzzy membership is modified using Eq. (12). After the membership value is modified defuzzification process is applied with the help of Eq. (13). Denoised coefficients are.

  6. 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...

  7. Fuzzy control and identification

    CERN Document Server

    Lilly, John H

    2010-01-01

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

  8. Fuzzy multi-criteria approach to ordering policy ranking in a supply chain

    Directory of Open Access Journals (Sweden)

    Tadić Danijela

    2005-01-01

    Full Text Available In this paper, a new fuzzy multi-criteria mathematical model for the selection of the best among a finite number of ordering policy of raw material in a supply chain is developed. The problem treated is a part of the purchasing plan of a company in an uncertain environment and it is very common in business practice. Optimization criteria selected describe the performance measures of ordering policies and generally their relative importance is different. It is assumed that the values of the optimization criteria are vague and imprecise. They are described by discrete fuzzy numbers and by linguistic expressions. The linguistic expressions are modeled by discrete fuzzy sets. The measures of belief that one ordering policy is better than another are defined by comparing fuzzy numbers. An illustrative example is given.

  9. Hybrid neural network and fuzzy logic approaches for rendezvous and capture in space

    Science.gov (United States)

    Berenji, Hamid R.; Castellano, Timothy

    1991-01-01

    The nonlinear behavior of many practical systems and unavailability of quantitative data regarding the input-output relations makes the analytical modeling of these systems very difficult. On the other hand, approximate reasoning-based controllers which do not require analytical models have demonstrated a number of successful applications such as the subway system in the city of Sendai. These applications have mainly concentrated on emulating the performance of a skilled human operator in the form of linguistic rules. However, the process of learning and tuning the control rules to achieve the desired performance remains a difficult task. Fuzzy Logic Control is based on fuzzy set theory. A fuzzy set is an extension of a crisp set. Crisp sets only allow full membership or no membership at all, whereas fuzzy sets allow partial membership. In other words, an element may partially belong to a set.

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

    National Research Council Canada - National Science Library

    Udupa, Jayaram

    2001-01-01

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

  11. 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.

  12. New Management Whole Process Evaluation of DSM Projects Based on Fuzzy-AHP Approach

    OpenAIRE

    Xiaoli Zhu; Mingjuan Ma; Song Xue; Dinglin Li; Ming Zeng

    2013-01-01

    In order to promote the development of DSM projects, it is necessary to establish a management evaluation indicator system considering whole process. This study analyzes key factors of every stage of DSM projects combining with the whole process theory and proposes a new evaluation indicator system of DSM projects management. Also we use fuzzy analytic hierarchy process which combines analytic hierarchy process and fuzzy comprehensive evaluation method to evaluate DSM projects management cons...

  13. 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

  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.

  15. 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.

  16. 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.

  17. Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

    Science.gov (United States)

    Dominguez, Jesus A.; Klinko, Steven J.

    2004-01-01

    A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

  18. Risk Assessment of Wastewater Collection Performance Using the Fuzzy Decision-making Approach

    Directory of Open Access Journals (Sweden)

    Maedeh Asgarian

    2015-10-01

    Full Text Available Wastewater collection network simulation in normal conditions dose not provide performance assessment in unusual circumstances. In this paper, a model has been developed for risk assessment of wastewater collection systems to manage their performance under natural or man-made critical conditions. In this model, certain criteria were defined, fuzzy MADM techniques were exploited, and a questionnaire was employed to measure such risk parameters as the probability of threats, the severity of their impacts, and the vulnerability of the network components. Based on the calculated magnitude of the risks, the threats and hazards were classified into groups ranging from low-risk to high-risk threats. The approaches adopted to combat the risks were also classified into the following three categories: "to deal with the risk", "risk shifting", and "risk taking". This process was implemented for the wastewater collection system in Shahrak-Gharb District in Tehran as a case study. ‘Introduction of chemical pollutants into the sewers’ and ‘drastic changes in wastewater quality’ were identified as the most threatening crises for the district and the ‘risk reduction strategy’ was proposed for combating the critical conditions in this district.

  19. Estimating oxygen consumption from heart rate using adaptive neuro-fuzzy inference system and analytical approaches.

    Science.gov (United States)

    Kolus, Ahmet; Dubé, Philippe-Antoine; Imbeau, Daniel; Labib, Richard; Dubeau, Denise

    2014-11-01

    In new approaches based on adaptive neuro-fuzzy systems (ANFIS) and analytical method, heart rate (HR) measurements were used to estimate oxygen consumption (VO2). Thirty-five participants performed Meyer and Flenghi's step-test (eight of which performed regeneration release work), during which heart rate and oxygen consumption were measured. Two individualized models and a General ANFIS model that does not require individual calibration were developed. Results indicated the superior precision achieved with individualized ANFIS modelling (RMSE = 1.0 and 2.8 ml/kg min in laboratory and field, respectively). The analytical model outperformed the traditional linear calibration and Flex-HR methods with field data. The General ANFIS model's estimates of VO2 were not significantly different from actual field VO2 measurements (RMSE = 3.5 ml/kg min). With its ease of use and low implementation cost, the General ANFIS model shows potential to replace any of the traditional individualized methods for VO2 estimation from HR data collected in the field. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  20. An Ontological-Fuzzy Approach to Advance Reservation in Multi-Cluster Grids

    International Nuclear Information System (INIS)

    Ferreira, D J; Dantas, M A R; Bauer, Michael A

    2010-01-01

    Advance reservation is an important mechanism for a successful utilization of available resources in distributed multi-cluster environments. This mechanism allows, for example, a user to provide parameters aiming to satisfy requirements related to applications' execution time and temporal dependence. This predictability can lead the system to reach higher levels of QoS. However, the support for advance reservation has been restricted due to the complexity of large scale configurations and also dynamic changes verified in these systems. In this research work it is proposed an advance reservation method, based on a ontology-fuzzy approach. It allows a user to reserve a wide variety of resources and enable large jobs to be reserved among different nodes. In addition, it dynamically verifies the possibility of reservation with the local RMS, avoiding future allocation conflicts. Experimental results of the proposal, through simulation, indicate that the proposed mechanism reached a successful level of flexibility for large jobs and more appropriated distribution of resources in a distributed multi-cluster configuration.

  1. Indexing the Environmental Quality Performance Based on A Fuzzy Inference Approach

    Science.gov (United States)

    Iswari, Lizda

    2018-03-01

    Environmental performance strongly deals with the quality of human life. In Indonesia, this performance is quantified through Environmental Quality Index (EQI) which consists of three indicators, i.e. river quality index, air quality index, and coverage of land cover. The current of this instrument data processing was done by averaging and weighting each index to represent the EQI at the provincial level. However, we found EQI interpretations that may contain some uncertainties and have a range of circumstances possibly less appropriate if processed under a common statistical approach. In this research, we aim to manage the indicators of EQI with a more intuitive computation technique and make some inferences related to the environmental performance in 33 provinces in Indonesia. Research was conducted in three stages of Mamdani Fuzzy Inference System (MAFIS), i.e. fuzzification, data inference, and defuzzification. Data input consists of 10 environmental parameters and the output is an index of Environmental Quality Performance (EQP). Research was applied to the environmental condition data set in 2015 and quantified the results into the scale of 0 to 100, i.e. 10 provinces at good performance with the EQP above 80 dominated by provinces in eastern part of Indonesia, 22 provinces with the EQP between 80 to 50, and one province in Java Island with the EQP below 20. This research shows that environmental quality performance can be quantified without eliminating the natures of the data set and simultaneously is able to show the environment behavior along with its spatial pattern distribution.

  2. Presenting Knowledge Management Implementation Model with Fuzzy Approach in Information Technology Industry

    Directory of Open Access Journals (Sweden)

    Zahra Razmi

    2015-12-01

    Full Text Available With the progress of modern sciences and more competitive becoming environment in the technology era, knowledge management is being counted as one of the most important stable competitive advantages of technology oriented organizations. This matter is of higher importance in high technology organizations, especially those active in information technology field due to their unique identity. This way, knowledge management has been already shifted to one of the most important priorities of such organizations that in case of not identifying, applying, recording and creating that knowledge, the organization is inevitable to pay fortunesto revive the knowledge gone. The purpose of this research is presenting a comprehensive knowledge management implementation model in information technology industry. Therefore, the measures of the suggested research’s model were identified by studying identical researches and projects done in knowledge management and information technology sector and also through consultation with the experts. This way, a questionnaire was designed in two parts and distributed among experts in the understudied organizations. The research’s data were analyzed through T Test and Binomial Test through fuzzy approach due to the constraints presented by the Lickert scale. The research findings demonstrate that the stages of knowledge management implementation model in information technology sector include knowledge evaluation, knowledge leverage, knowledge planning, knowledge culture, knowledge strategies, knowledge management processes, suitable knowledge infrastructures, knowledge organization and knowledge presentation. There also exist actions in each stage that effect successful implementation of the mentioned stages.

  3. Cooperative fuzzy games approach to setting target levels of ECs in quality function deployment.

    Science.gov (United States)

    Yang, Zhihui; Chen, Yizeng; Yin, Yunqiang

    2014-01-01

    Quality function deployment (QFD) can provide a means of translating customer requirements (CRs) into engineering characteristics (ECs) for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.

  4. 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.

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

    International Nuclear Information System (INIS)

    Sabahi, Kamel; Teshnehlab, Mohammad; Shoorhedeli, Mahdi Aliyari

    2009-01-01

    In this study, a new adaptive controller based on modified feedback error learning (FEL) approaches is proposed for load frequency control (LFC) problem. The FEL strategy consists of intelligent and conventional controllers in feedforward and feedback paths, respectively. In this strategy, a conventional feedback controller (CFC), i.e. proportional, integral and derivative (PID) controller, is essential to guarantee global asymptotic stability of the overall system; and an intelligent feedforward controller (INFC) is adopted to learn the inverse of the controlled system. Therefore, when the INFC learns the inverse of controlled system, the tracking of reference signal is done properly. Generally, the CFC is designed at nominal operating conditions of the system and, therefore, fails to provide the best control performance as well as global stability over a wide range of changes in the operating conditions of the system. So, in this study a supervised controller (SC), a lookup table based controller, is addressed for tuning of the CFC. During abrupt changes of the power system parameters, the SC adjusts the PID parameters according to these operating conditions. Moreover, for improving the performance of overall system, a recurrent fuzzy neural network (RFNN) is adopted in INFC instead of the conventional neural network, which was used in past studies. The proposed FEL controller has been compared with the conventional feedback error learning controller (CFEL) and the PID controller through some performance indices

  6. 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.

  7. 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.

  8. An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach.

    Science.gov (United States)

    Ahmadvand, Sahar; Pishvaee, Mir Saman

    2017-08-09

    Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem. Eligible patient-kidney pairs are regarded as decision making units (DMUs) in a Credibility-based Fuzzy Common Weights DEA (CFCWDEA) approach and are ranked based on efficiency scores. Using a common set of weights for all DMUs ensures a high degree of fairness in the assessment and ranking of DMUs. The proposed model is also the first allocation method capable of coping with the vague and intervallic medical and nonmedical allocation factors by the aid of fuzzy programming. Verification and validation of the proposed approach are performed in two steps using a real case study from the Iranian kidney allocation system. First, the superiority of the proposed deterministic model in enhancing allocation outcomes is demonstrated and analyzed. Second, the applicability of the proposed fuzzy DEA method is demonstrated using a series of data realizations for different credibility levels.

  9. Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

    Directory of Open Access Journals (Sweden)

    Y. H. Subagadis

    2014-09-01

    Full Text Available The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water–society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

  10. Assessment of Tribological performance of Coconut Shell Ash Particle Reinforced Al-Si-Fe Composites using Grey-Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    R.S.S. Raju

    2017-09-01

    Full Text Available The paper investigates optimization of wear behaviour of coconut shell ash (CSA reinforced aluminium composites using pin-on-disc setup. The experiments were carried out with three process parameters: Load, percentage (% of CSA and sliding distance. Three adequate responses: wear (µm, wear rate (mm3/m and coefficient of friction were considered. In this study, a hybrid approach (i.e. Grey-Fuzzy has been applied to optimizing the several responses. The fuzzy logic concept has been used for handling the uncertainty in the decision-making process. Analysis of variance (ANOVA discloses that the highest influencing parameter was load, followed by sliding distance and % of CSAp to the overall tribological performance.

  11. Evaluation model of project complexity for large-scale construction projects in Iran - A Fuzzy ANP approach

    Directory of Open Access Journals (Sweden)

    Aliyeh Kazemi

    2016-09-01

    Full Text Available Construction projects have always been complex. By growing trend of this complexity, implementations of large-scale constructions become harder. Hence, evaluating and understanding these complexities are critical. Correct evaluation of a project complication can provide executives and managers with good source to use. Fuzzy analytic network process (ANP is a logical and systematic approach toward defining, evaluation, and grading. This method allows for analyzing complex systems, and determining complexity of them. In this study, by taking advantage of fuzzy ANP, effective indexes for development of complications in large-scale construction projects in Iran have been determined and prioritized. The results show socio-political, project system interdependencies, and technological complexity indexes ranked top to three. Furthermore, in comparison of three main huge projects: commercial-administrative, hospital, and skyscrapers, the hospital project had been evaluated as the most complicated. This model is beneficial for professionals in managing large-scale projects.

  12. 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.

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

    International Nuclear Information System (INIS)

    Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan

    2016-01-01

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

  14. Optimal expansion of water quality monitoring network by fuzzy optimization approach.

    Science.gov (United States)

    Ning, Shu-Kuang; Chang, Ni-Bin

    2004-02-01

    River reaches are frequently classified with respect to various mode of water utilization depending on the quantity and quality of water resources available at different location. Monitoring of water quality in a river system must collect both temporal and spatial information for comparison with respect to the preferred situation of a water body based on different scenarios. Designing a technically sound monitoring network, however, needs to identify a suite of significant planning objectives and consider a series of inherent limitations simultaneously. It would rely on applying an advanced systems analysis technique via an integrated simulation-optimization approach to meet the ultimate goal. This article presents an optimal expansion strategy of water quality monitoring stations for fulfilling a long-term monitoring mission under an uncertain environment. The planning objectives considered in this analysis are to increase the protection degree in the proximity of the river system with higher population density, to enhance the detection capability for lower compliance areas, to promote the detection sensitivity by better deployment and installation of monitoring stations, to reflect the levels of utilization potential of water body at different locations, and to monitor the essential water quality in the upper stream areas of all water intakes. The constraint set contains the limitations of budget, equity implication, and the detection sensitivity in the water environment. A fuzzy multi-objective evaluation framework that reflects the uncertainty embedded in decision making is designed for postulating and analyzing the underlying principles of optimal expansion strategy of monitoring network. The case study being organized in South Taiwan demonstrates a set of more robust and flexible expansion alternatives in terms of spatial priority. Such an approach uniquely indicates the preference order of each candidate site to be expanded step-wise whenever the budget

  15. APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

    Directory of Open Access Journals (Sweden)

    Dušan Petković

    2017-04-01

    Full Text Available Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems.

  16. Generalized interval-valued fuzzy variable precision rough sets determined by fuzzy logical operators

    Science.gov (United States)

    Qing Hu, Bao

    2015-11-01

    The fuzzy rough set model and interval-valued fuzzy rough set model have been introduced to handle databases with real values and interval values, respectively. Variable precision rough set was advanced by Ziarko to overcome the shortcomings of misclassification and/or perturbation in Pawlak rough sets. By combining fuzzy rough set and variable precision rough set, a variety of fuzzy variable precision rough sets were studied, which cannot only handle numerical data, but are also less sensitive to misclassification. However, fuzzy variable precision rough sets cannot effectively handle interval-valued data-sets. Research into interval-valued fuzzy rough sets for interval-valued fuzzy data-sets has commenced; however, variable precision problems have not been considered in interval-valued fuzzy rough sets and generalized interval-valued fuzzy rough sets based on fuzzy logical operators nor have interval-valued fuzzy sets been considered in variable precision rough sets and fuzzy variable precision rough sets. These current models are incapable of wide application, especially on misclassification and/or perturbation and on interval-valued fuzzy data-sets. In this paper, these models are generalized to a more integrative approach that not only considers interval-valued fuzzy sets, but also variable precision. First, we review generalized interval-valued fuzzy rough sets based on two fuzzy logical operators: interval-valued fuzzy triangular norms and interval-valued fuzzy residual implicators. Second, we propose generalized interval-valued fuzzy variable precision rough sets based on the above two fuzzy logical operators. Finally, we confirm that some existing models, including rough sets, fuzzy variable precision rough sets, interval-valued fuzzy rough sets, generalized fuzzy rough sets and generalized interval-valued fuzzy variable precision rough sets based on fuzzy logical operators, are special cases of the proposed models.

  17. A new approach to the statistical treatment of 2D-maps in proteomics using fuzzy logic.

    Science.gov (United States)

    Marengo, Emilio; Robotti, Elisa; Gianotti, Valentina; Righetti, Pier Giorgio

    2003-01-01

    A new approach to the statistical treatment of 2D-maps has been developed. This method is based on the use of fuzzy logic and allows to take into consideration the typical low reproducibility of 2D-maps. In this approach the signal corresponding to the presence of proteins on the 2D-maps is substituted with probability functions, centred on the signal itself. The standard deviation of the bidimensional gaussian probability function employed to blur the signal allows to assign different uncertainties to the two electrophoretic dimensions. The effect of changing the standard deviation and the digitalisation resolution are investigated.

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

    Science.gov (United States)

    Jarre, Astrid; Paterson, Barbara; Moloney, Coleen L.; Miller, David C. M.; Field, John G.; Starfield, Anthony M.

    2008-10-01

    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 rule-based Boolean and fuzzy-logic models have been used successfully as knowledge-based decision support tools. This study compares two such systems relevant to fisheries management in an EAF developed for the southern Benguela. The first is a rule-based system for the prediction of anchovy recruitment and the second is a fuzzy-logic tool to monitor implementation of an EAF in the sardine fishery. We construct a fuzzy-logic counterpart to the rule-based model, and a rule-based counterpart to the fuzzy-logic model, compare their results, and include feedback from potential users of these two 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 visualization of intermediate and end results is an important advantage of any system. Applying the two approaches in parallel improved our understanding of the model as well as of the underlying problems. Even for complex problems, small knowledge-based systems such as the ones explored here are worth developing and using. Their strengths lie in (i) synthesis of the problem in a logical and transparent framework, (ii) helping scientists to deliberate how to apply their science to

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Nuclear reactor control with fuzzy logic approaches - strengths, weakness, opportunities, and threats

    International Nuclear Information System (INIS)

    Ruan, Da

    2004-01-01

    As part of the special track on 'Lessons learned from computational intelligence in nuclear applications' at the forthcoming FLINS 2004 conference on Applied Computational Intelligence (Blankenberge, Belgium, September 1-3, 2004), research experiences on fuzzy logic techniques in applications of nuclear reactor control operation are critically reviewed in this presentation. Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined thought a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK-CEN) and the Mexican Nuclear Centre (ININ) on the fuzzy logic control for nuclear reactor control project under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (Author)

  2. A fuzzy analytic hierarchy process approach for assessing national competitiveness in the hydrogen technology sector

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seong Kon; Kim, Jong Wook [Energy Policy Research Division, Korea Institute of Energy Research, 71-2 Jang-dong, Yuseong-gu, Daejeon 305-343 (Korea); Mogi, Gento [Department of Technology Management for Innovation, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Gim, Bong Jin [Department of Industrial Engineering, Dankook University, San 29, Anseo-dong, Cheonan-si, Chungnam 330-714 (Korea)

    2008-12-15

    As it is more environmentally sound and friendly than conventional energy technologies that emit carbon dioxide, hydrogen technology can play a key role in solving the problems caused by the greenhouse gas effect and in coping with the hydrogen economy. Numerous countries around the world, including Korea, have increasingly focused on R and D where hydrogen technology development is concerned. This paper focuses on the use of the fuzzy analytic hierarchy process (fuzzy AHP), which is an extension of the AHP method and uses interval values to reflect the vagueness of human thought, to assess national competitiveness in the hydrogen technology sector. This analysis based on the AHP and fuzzy AHP methods revealed that Korea ranked 6th in terms of national competitiveness in the hydrogen technology sector. (author)

  3. Application of MCDM based hybrid optimization tool during turning of ASTM A588

    Directory of Open Access Journals (Sweden)

    Himadri Majumder

    2017-07-01

    Full Text Available Multi-criteria decision making approach is one of the most troublesome tools for solving the tangled optimization problems in the machining area due to its capability of solving the complex optimization problems in the production process. Turning is widely used in the manufacturing processes as it offers enormous advantages like good quality product, customer satisfaction, economical and relatively easy to apply. A contemporary approach, MOORA coupled with PCA, was used to ascertain an optimal combination of input parameters (spindle speed, depth of cut and feed rate for the given output parameters (power consumption, average surface roughness and frequency of tool vibration using L27 orthogonal array for turning on ASTM A588 mild steel. Comparison between MOORA-PCA and TOPSIS-PCA shows the effectiveness of MOORA over TOPSIS method. The optimum parameter combination for multi-performance characteristics has been established for ASTM A588 mild steel are spindle speed 160 rpm, depth of cut 0.1 mm and feed rate 0.08 mm/rev. Therefore, this study focuses on the application of the hybrid MCDM approach as a vital selection making tool to deal with multi objective optimization problems.

  4. Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage.

    Science.gov (United States)

    Zhang, Limao; Wu, Xianguo; Qin, Yawei; Skibniewski, Miroslaw J; Liu, Wenli

    2016-02-01

    Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel-induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step-by-step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN-based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel-induced pipeline damage model is proposed to reveal the cause-effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment. © 2015 Society for Risk Analysis.

  5. A neuro-fuzzy approach for predicting hemodynamic responses during anesthesia.

    Science.gov (United States)

    Nunes, Catarina S; Amorim, Pedro

    2008-01-01

    The effect of drugs' interaction on the hemo-dynamic variables is of great importance when considering patient's safety and stability. It is also important for control infusion systems during anesthesia. In this article, an adaptive-network fuzzy inference system is used to model the effect of two drugs (propofol and remifentanil) on the mean arterial pressure and heart rate. The clinical data of 45 patients is used to train and test the model. The use of subtractive clustering improved the model performance on the testing data set. The fuzzy model is able to capture the synergistic interaction between the two drugs, but other influences were detected.

  6. Fuzzy Set Field and Fuzzy Metric

    OpenAIRE

    Gebray, Gebru; Reddy, B. Krishna

    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.

  7. 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.

  8. A Divide-and-Conquer Approach for Solving Fuzzy Max-Archimedean t-Norm Relational Equations

    Directory of Open Access Journals (Sweden)

    Jun-Lin Lin

    2014-01-01

    Full Text Available A system of fuzzy relational equations with the max-Archimedean t-norm composition was considered. The relevant literature indicated that this problem can be reduced to the problem of finding all the irredundant coverings of a binary matrix. A divide-and-conquer approach is proposed to solve this problem and, subsequently, to solve the original problem. This approach was used to analyze the binary matrix and then decompose the matrix into several submatrices such that the irredundant coverings of the original matrix could be constructed using the irredundant coverings of each of these submatrices. This step was performed recursively for each of these submatrices to obtain the irredundant coverings. Finally, once all the irredundant coverings of the original matrix were found, they were easily converted into the minimal solutions of the fuzzy relational equations. Experiments on binary matrices, with the number of irredundant coverings ranging from 24 to 9680, were also performed. The results indicated that, for test matrices that could initially be partitioned into more than one submatrix, this approach reduced the execution time by more than three orders of magnitude. For the other test matrices, this approach was still useful because certain submatrices could be partitioned into more than one submatrix.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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 internat...... 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.......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...

  11. A New Controlling Approach of Type 1 Diabetics Based on Interval Type-2 Fuzzy Controller

    Directory of Open Access Journals (Sweden)

    Nafiseh Mollaei

    2014-09-01

    Full Text Available Augmented Minimal Model which is developed in consideration of the patient is taken into attention and uncertainties in this model which can occur by factors such as blood glucose, daily meals or sudden stress in considered. In addition to eliminate the effects of uncertainty, different control methods may be utilized. In this article, fuzzy control as a logical tool is used to transform words into control actions. To enhance the system performance, an interval type-2 Fuzzy controller has been implemented. To date, because of computational complexity of using a general type-2 fuzzy set (T2 FS in a T2 fuzzy logic system (FLS, most people only use an interval T2 FS, the result being an interval T2 FLS (IT2 FLS. A daily meal disturbance is injected to model to consider the real environment for simulation. Finally, the control method tuned by standard tuning procedure and simulation results show the efficiency of method in regulating the blood glucose level in presentment of daily meal disturbance.

  12. Minimal sensor count approach to fuzzy logic rotary blood pump flow control.

    Science.gov (United States)

    Casas, Fernando; Ahmed, Nisar; Reeves, Andrew

    2007-01-01

    A rotary blood pump fuzzy logic flow controller without flow sensors was developed and tested in vitro. The controller, implemented in LabView, was set to maintain a flow set point in the presence of external pressure disturbances. Flow was estimated as a function of measured pump's delta P and speed, using a steady-state, nonlinear approximation. The fuzzy controller used the pump's flow estimate and delta P as feedback variables. The defuzzified control output manipulated the pump speed. Membership functions included flow error, delta P, and pump speed. Experimental runs in a mock loop (water/glycerin 3.5 cPs, 37 degrees C), using the estimated flow, were compared with those using a Transonic flow meter for nine conditions of flow and delta P (4 to 6 L/min, 150 to 350 mm Hg). Pressure disturbances generated by a servo pinch valve ranged from +/-23 to +/-47 mm Hg. Results indicated that the fuzzy controller ably regulated the flow set point to within +/-10% of the baseline even under large swings in pressure. There was no difference in controller performance between the ultrasonic flow measurement and the estimated flow calculation scenarios. These tests demonstrated that the fuzzy controller is capable of rejecting disturbances and regulating flow to acceptable limits while using a flow estimate.

  13. A Hierarchy Fuzzy MCDM Method for Studying Electronic Marketing Strategies in the Information Service Industry.

    Science.gov (United States)

    Tang, Michael T.; Tzeng, Gwo-Hshiung

    In this paper, the impacts of Electronic Commerce (EC) on the international marketing strategies of information service industries are studied. In seeking to blend humanistic concerns in this research with technological development by addressing challenges for deterministic attitudes, the paper examines critical environmental factors relevant to…

  14. Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

    Directory of Open Access Journals (Sweden)

    Han Songshan

    2015-02-01

    Full Text Available A fuzzy robust nonlinear controller for hydraulic rotary actuators in flight motion simulators is proposed. Compared with other three-order models of hydraulic rotary actuators, the proposed controller based on first-order nonlinear model is more easily applied in practice, whose control law is relatively simple. It not only does not need high-order derivative of desired command, but also does not require the feedback signals of velocity, acceleration and jerk of hydraulic rotary actuators. Another advantage is that it does not rely on any information of friction, inertia force and external disturbing force/torque, which are always difficult to resolve in flight motion simulators. Due to the special composite vane seals of rectangular cross-section and goalpost shape used in hydraulic rotary actuators, the leakage model is more complicated than that of traditional linear hydraulic cylinders. Adaptive multi-input single-output (MISO fuzzy compensators are introduced to estimate nonlinear uncertain functions about leakage and bulk modulus. Meanwhile, the decomposition of the uncertainties is used to reduce the total number of fuzzy rules. Different from other adaptive fuzzy compensators, a discontinuous projection mapping is employed to guarantee the estimation process to be bounded. Furthermore, with a sufficient number of fuzzy rules, the controller theoretically can guarantee asymptotic tracking performance in the presence of the above uncertainties, which is very important for high-accuracy tracking control of flight motion simulators. Comparative experimental results demonstrate the effectiveness of the proposed algorithm, which can guarantee transient performance and better final accurate tracking in the presence of uncertain nonlinearities and parametric uncertainties.

  15. Study of decision framework of wind farm project plan selection under intuitionistic fuzzy set and fuzzy measure environment

    International Nuclear Information System (INIS)

    Wu, Yunna; Geng, Shuai; Xu, Hu; Zhang, Haobo

    2014-01-01

    Highlights: • Experts’ opinions are expressed by using the intuitionistic fuzzy values. • Fuzzy measure is used to solve the dependence problem of criteria. • The compensatory problem of performance scores is reasonably processed. - Abstract: Project selection plays an important role in the entire life cycle of wind farm project and the multi-criteria decision making (MCDM) methods are very important in the whole wind farm project plan selection process. There are problems in the present MCDM methods decrease evaluation quality of the wind farm project plans: first, the information loss exists in the wind farm project plan evaluation process. Second, it is difficult to satisfy the independent assumption of the multi-criteria decision making methods used in the wind farm project plan evaluation in fact. Third, the compensatory problem of performance scores of the wind farm project plans is processed unreasonably. Hence the innovation points of this paper are as follows: first, the intuitionistic fuzzy numbers are used instead of fuzzy numbers or numerical values to reflect the experts’ intuitive preferences to decrease the probability of information loss; second, the fuzzy measure is used to rate the important degrees of criteria in order to avoid the independent assumption and to increase the reasonability; third, the partial compensatory problem of performance scores is well processed by using intuitionistic fuzzy Choquet (IFC) operator and generalized intuitionistic fuzzy ordered geometric averaging (GIFOGA) operator. These operators can deal with the compensatory performance scores and non-compensatory performance scores respectively. Finally, a case study demonstrates the effectiveness of decision framework

  16. A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry

    2014-01-01

    Highlights: • We propose a fuzzy-based reliability approach to evaluate basic event reliabilities. • It implements the concepts of failure possibilities and fuzzy sets. • Experts evaluate basic event failure possibilities using qualitative words. • Triangular fuzzy numbers mathematically represent qualitative failure possibilities. • It is a very good alternative for conventional reliability approach. - Abstract: Fault tree analysis has been widely utilized as a tool for nuclear power plant probabilistic safety assessment. This analysis can be completed only if all basic events of the system fault tree have their quantitative failure rates or failure probabilities. However, it is difficult to obtain those failure data due to insufficient data, environment changing or new components. This study proposes a fuzzy-based reliability approach to evaluate basic events of system fault trees whose failure precise probability distributions of their lifetime to failures are not available. It applies the concept of failure possibilities to qualitatively evaluate basic events and the concept of fuzzy sets to quantitatively represent the corresponding failure possibilities. To demonstrate the feasibility and the effectiveness of the proposed approach, the actual basic event failure probabilities collected from the operational experiences of the David–Besse design of the Babcock and Wilcox reactor protection system fault tree are used to benchmark the failure probabilities generated by the proposed approach. The results confirm that the proposed fuzzy-based reliability approach arises as a suitable alternative for the conventional probabilistic reliability approach when basic events do not have the corresponding quantitative historical failure data for determining their reliability characteristics. Hence, it overcomes the limitation of the conventional fault tree analysis for nuclear power plant probabilistic safety assessment

  17. Using fuzzy analytical hierarchy process (AHP to evaluate web development platform

    Directory of Open Access Journals (Sweden)

    Ahmad Sarfaraz

    2012-01-01

    Full Text Available Web development is plays an important role on business plans and people's lives. One of the key decisions in which both short-term and long-term success of the project depends is choosing the right development platform. Its criticality can be judged by the fact that once a platform is chosen, one has to live with it throughout the software development life cycle. The entire shape of the project depends on the language, operating system, tools, frameworks etc., in short the web development platform chosen. In addition, choosing the right platform is a multi criteria decision making (MCDM problem. We propose a fuzzy analytical hierarchy process model to solve the MCDM problem. We try to tap the real-life modeling potential of fuzzy logic and conjugate it with the commonly used powerful AHP modeling method.

  18. Identification of drought in Dhalai river watershed using MCDM and ANN models

    Science.gov (United States)

    Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

    2017-03-01

    An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

  19. Design and Development of Decision Making System Using Fuzzy Analytic Hierarchy Process

    OpenAIRE

    Chin W. Cheong; Lee H. Jie; Mak C. Meng; Amy L.H. Lan

    2008-01-01

    This article aims to develop a fuzzy Multicriteria Decision Making (MCDM) tool that equips with Analytic Hierarchy Process (AHP) framework to help users in semi-structured and unstructured decision making tasks. The tool provides portability and adaptability features by deploying the software on web platform. In addition, this system provides an integrated domain reference channel via a database connection to assist the user obtains relevant information regarding the problem domain before con...

  20. The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning

    Science.gov (United States)

    Hattab, Tarek; Ben Rais Lasram, Frida; Albouy, Camille; Sammari, Chérif; Romdhane, Mohamed Salah; Cury, Philippe; Leprieur, Fabien; Le Loc’h, François

    2013-01-01

    Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study. PMID:24146867

  1. A Fuzzy-Grey Multicriteria Decision Making Approach for Green Supplier Selection in Low-Carbon Supply Chain

    Directory of Open Access Journals (Sweden)

    Qinghua Pang

    2017-01-01

    Full Text Available Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.

  2. Granular, soft and fuzzy approaches for intelligent systems dedicated to professor Ronald R. Yager

    CERN Document Server

    Filev, Dimitar; Beliakov, Gleb

    2017-01-01

    This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communit...

  3. Fuzzy approach to business improvement of holding equipment in the conditions of decreased production range

    Directory of Open Access Journals (Sweden)

    Tadić Branko

    2007-01-01

    Full Text Available In recent years, manufacturing industry has been characterized by a decreased production range and a demand for a rapid change of production programs. In such conditions holding equipment costs are considerably larger. In this paper, we review and analyze possible ways of business improvement concerning holding equipment in specific production conditions characterized by the decreased production range and lack of financial sources for applying systems of assembled and disassembled equipment. Classification of elements and group of elements of those systems is performed by applying a new fuzzy ABC method presented in this paper. Selected optimization criteria describe the performance measures of elements and group of elements of assembled and disassembled equipment whereas their relative weights are not the same. It is assumed that the values of imprecise optimization criteria and their relative weights are described by discrete fuzzy numbers. The developed procedure is illustrated by an example with real input data.

  4. Improved Approach to Robust Control for Type-2 T-S Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Bum Yong Park

    2018-01-01

    Full Text Available This paper is concerned with the robust stability conditions to stabilize the type 2 Takagi-Sugeno (T-S fuzzy systems. The conditions effectively handle parameter uncertainties using lower and upper membership functions. To improve the solvability of the stability conditions, we establish a multigain controller with comprehensive information of the lower and upper membership grades. In addition, a well-organized relaxation technique is proposed to fully exploit relationship among fuzzy weighting functions and their lower and upper membership grades, which enlarges a set of feasible solutions. Therefore, we derive a less conservative stabilization condition in terms of linear matrix inequalities (LMIs than those in the literature. Two simulation examples illustrate the effectiveness and robustness of the derived stabilization conditions.

  5. Fuzzy approach for improved recognition of citric acid induced piglet coughing from continuous registration

    Science.gov (United States)

    Van Hirtum, A.; Berckmans, D.

    2003-09-01

    A natural acoustic indicator of animal welfare is the appearance (or absence) of coughing in the animal habitat. A sound-database of 5319 individual sounds including 2034 coughs was collected on six healthy piglets containing both animal vocalizations and background noises. Each of the test animals was repeatedly placed in a laboratory installation where coughing was induced by nebulization of citric acid. A two-class classification into 'cough' or 'other' was performed by the application of a distance function to a fast Fourier spectral sound analysis. This resulted in a positive cough recognition of 92%. For the whole sound-database however there was a misclassification of 21%. As spectral information up to 10000 Hz is available, an improved overall classification on the same database is obtained by applying the distance function to nine frequency ranges and combining the achieved distance-values in fuzzy rules. For each frequency range clustering threshold is determined by fuzzy c-means clustering.

  6. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    Science.gov (United States)

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

    2017-12-01

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

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

    OpenAIRE

    B.C. Routar; A.K. Sahoo; Akshay K. Rout; A. K. Parida; J. R. Behera

    2013-01-01

    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 ...

  8. A fuzzy approach to evaluation and management of therapeutic procedure in diabetes mellitus treatment

    Directory of Open Access Journals (Sweden)

    Tadić Danijela

    2010-01-01

    Full Text Available In this paper a new fuzzy model (FMOTPD2 is developed and by this model the measures of beliefs are determined so that one of the groups of possible therapeutic procedures is optimal for each patient of type 2 diabetes on hospital treatment. The choice of therapeutic procedure on individual level, which is one of the demands of modern medicine, means that each therapeutic procedure is to be evaluated by multiple and different criteria. In this paper, evaluation criteria are classified into two groups: (1 common criteria by which medicines used by the type 2 diabetes patients are being evaluated and (2 specific criteria, by which the patients' 1h state of health with type 2 diabetes mellitus is being estimated. Generally, the relative importance and values of these criteria are different. It is assumed that (a the relative importance of evaluation criteria is defined by a team of medical experts and described by linguistic expressions and (b the values of evaluation criteria are determined by evidence data, anamnesis and a diagnostic process. They can be crisp or uncertain. The most often used linguistic expressions describing the relative importance of evaluation criteria are modeled by triangular fuzzy numbers. The rest of uncertainties, which exist in developed model are described by discrete fuzzy numbers. A new algorithm for determining a unified fuzzy portrait of treated therapeutic procedures for each patient is given. It enables calculation of the measures of beliefs that some therapeutic procedures are more optimal than the others. The developed model is illustrated by examples with real word data collected in a hospital.

  9. Fractional variational problems and particle in cell gyrokinetic simulations with fuzzy logic approach for tokamaks

    Directory of Open Access Journals (Sweden)

    Rastović Danilo

    2009-01-01

    Full Text Available In earlier Rastovic's papers [1] and [2], the effort was given to analyze the stochastic control of tokamaks. In this paper, the deterministic control of tokamak turbulence is investigated via fractional variational calculus, particle in cell simulations, and fuzzy logic methods. Fractional integrals can be considered as approximations of integrals on fractals. The turbulent media could be of the fractal structure and the corresponding equations should be changed to include the fractal features of the media.

  10. A HEURISTIC CASCADING FUZZY LOGIC APPROACH TO REACTIVE NAVIGATION FOR UAV

    OpenAIRE

    Yew-Chung Chak; Renuganth Varatharajoo

    2014-01-01

    ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs) safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines) and moving obstacles (e.g., aircraft, balloons). In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R) problem, in which the contro...

  11. 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

    -ceives. Fuzzeval employs an evaluation function that adjusts the membership functions linked to the linguistic variables in the knowledge base. The mem-bership functions are aligned to the average crisp input that was successfully used in the past winning games. Fuzzeval mechanisms are adaptive and have...... the simplicity associated with fuzzy controllers. Our experiments show that Fuzzeval improves its performance up to 42% after a match of only one hun-dred backgammon games played against Pubeval, a strong intermediate level program....

  12. Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches

    OpenAIRE

    H. Bonakdari; I. Ebtehaj

    2017-01-01

    The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN ...

  13. A Fuzzy PID Approach for the Vibration Control of the FSPM

    Directory of Open Access Journals (Sweden)

    Zhu-Feng Shao

    2013-01-01

    Full Text Available This paper focuses on the vibration control issue of a Flexibly Supported Parallel Manipulator (FSPM, which consists of a flexible support and a rigid parallel manipulator. The distinct characteristic of an FSPM is the dynamic coupling between the rigid and flexible parts, which challenges the vibration control implemented by the rigid parallel manipulator. The research object is a 40m scale model of the Feed Support System (FSS for the Five-hundred-meter Aperture Spherical radio Telescope (FAST project, which is composed of a cable-driven parallel manipulator, an A-B rotator and a rigid Stewart manipulator, assembled in series. The cable-driven parallel manipulator is sensitive to disturbances and could lead to system vibration with a large terminal error. The rigid Stewart manipulator is designed to carry out the vibration control. Considering the time-variability, nonlinearity and dynamic coupling of an FSPM, a fuzzy proportional–integral–derivative (PID controller is introduced. The fuzzy inference rules established on the terminal error and the error change are used to adjust the PID parameters to achieve better performance. Physical experiments are carried out and the results indicate that the fuzzy PID method can effectively promote the terminal precision and maintain system stability. The control methodology proposed in this paper is quite promising for the vibration control of an FSPM.

  14. Posturography stability score generation for stroke patient using Kinect: Fuzzy based approach.

    Science.gov (United States)

    Mazumder, Oishee; Chakravarty, Kingshuk; Chatterjee, Debatri; Sinha, Aniruddha; Das, Abhijit

    2017-07-01

    Aim of this paper is to formulate a posturography stability score for stroke patients using fuzzy logic. Postural instability is one of the prominent symptoms of stroke, dementia, parkinsons disease, myopathy, etc. and is the major precursor of fall. Conventional scoring techniques used to assess postural stability require manual intervention and are dependent on live interaction with physiotherapist. We propose a novel scoring technique to calculate static stability of a person using posturography features acquired by Kinect sensor, which do not require any manual intervention or expert guidance, is cost effective and hence are ideal for tele rehabilitation purpose. Stability analysis is done during Single Limb Stance (SLS) exercise. Kinect sensor is used to calculate three features, naming SLS duration, vibration index, calculated from mean vibration of twenty joints and sway area of Centre of Mass (CoM). Based on the variation of these features, a fuzzy rule base is generated which calculates a static stability score. One way analysis of variance (Anova) between a group of stroke population and healthy individuals under study validates the reliability of the proposed scorer. Generated fuzzy score are comparable with standard stability scorer like Berg Balance scale and fall risk assessment tool like Johns Hopkins scale. Stability score, besides providing an index of overall stability can also be used as a fall predictability index.

  15. Parameter identification of the glazed photovoltaic thermal system using Genetic Algorithm–Fuzzy System (GA–FS) approach and its comparative study

    International Nuclear Information System (INIS)

    Singh, Sonveer; Agrawal, Sanjay

    2015-01-01

    Highlights: • Optimization using Genetic Algorithm–Fuzzy System approach. • Overall exergy efficiency has been evaluated with different optimization tools. • Comparative analysis has been done. • GA–FS is very efficient and fast technique. • Overall exergy efficiency has been improved. - Abstract: In this paper, Genetic Algorithm–Fuzzy System (GA–FS) approach is used to identify the optimized parameters of the glazed photovoltaic thermal (PVT) system and to improve its overall exergy efficiency. The fuzzy knowledge base is used to improve the efficiency of Genetic Algorithm (GA). It is observed that three GA parameters, namely: (i) crossover probability (P cross ), (ii) mutation probability (P mut ) and (iii) population size are changing dynamically during the program, according to fuzzy knowledge base to maximize the efficiency of the GA. Here, overall exergy efficiency is considered as an objective function during the optimization process for GA–FS approach. The effort has been made to identify the different optimized parameters like; length and depth of the channel, velocity of flowing fluid, overall heat transfer coefficient from solar cell to ambient and flowing fluid and overall back loss heat transfer coefficient from flowing fluid to the ambient to maximize the overall exergy efficiency using GA–FS approach. Performance of glazed PVT using GA–FS approach has been compared with performance using GA approach and without GA. It has also been observed that the GA–FS approach is a better approach as compared to GA approach because it converges faster as compare to GA because the use of the fuzzy knowledge base with GA and take less time for identification of optimized system parameters.

  16. Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties.

    Science.gov (United States)

    Guo, P; Huang, G H

    2010-03-01

    In this study, an interval-parameter semi-infinite fuzzy-chance-constrained mixed-integer linear programming (ISIFCIP) approach is developed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing interval-parameter semi-infinite programming (ISIP) and fuzzy-chance-constrained programming (FCCP) by incorporating uncertainties expressed as dual uncertainties of functional intervals and multiple uncertainties of distributions with fuzzy-interval admissible probability of violating constraint within a general optimization framework. The binary-variable solutions represent the decisions of waste-management-facility expansion, and the continuous ones are related to decisions of waste-flow allocation. The interval solutions can help decision-makers to obtain multiple decision alternatives, as well as provide bases for further analyses of tradeoffs between waste-management cost and system-failure risk. In the application to the City of Regina, Canada, two scenarios are considered. In Scenario 1, the City's waste-management practices would be based on the existing policy over the next 25 years. The total diversion rate for the residential waste would be approximately 14%. Scenario 2 is associated with a policy for waste minimization and diversion, where 35% diversion of residential waste should be achieved within 15 years, and 50% diversion over 25 years. In this scenario, not only landfill would be expanded, but also CF and MRF would be expanded. Through the scenario analyses, useful decision support for the City's solid-waste managers and decision-makers has been generated. Three special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it is useful for tackling multiple uncertainties expressed as intervals, functional intervals, probability distributions, fuzzy sets, and their

  17. Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

    Directory of Open Access Journals (Sweden)

    Vicenc Torra

    2008-01-01

    Full Text Available WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them.

  18. MODELING OF INVESTMENT STRATEGIES IN STOCKS MARKETS: AN APPROACH FROM MULTI AGENT BASED SIMULATION AND FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    ALEJANDRO ESCOBAR

    2010-01-01

    Full Text Available This paper presents a simulation model of a complex system, in this case a financial market, using a MultiAgent Based Simulation approach. Such model takes into account microlevel aspects like the Continuous Double Auction mechanism, which is widely used within stock markets, as well as investor agents reasoning who participate looking for profits. To model such reasoning several variables were considered including general stocks information like profitability and volatility, but also some agent's aspects like their risk tendency. All these variables are incorporated throughout a fuzzy logic approach trying to represent in a faithful manner the kind of reasoning that nonexpert investors have, including a stochastic component in order to model human factors.

  19. A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications.

    Science.gov (United States)

    Costa, Daniel G; Collotta, Mario; Pau, Giovanni; Duran-Faundez, Cristian

    2017-01-05

    The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field.

  20. Fuzzy neural network quadratic stabilization output feedback control for biped robots via H/sub /spl infin// approach.

    Science.gov (United States)

    Liu, Zhi; Li, Chunwen

    2003-01-01

    A novel fuzzy neural network (FNN) quadratic stabilization output feedback control scheme is proposed for the trajectory tracking problems of biped robots with an FNN nonlinear observer. First, a robust quadratic stabilization FNN nonlinear observer is presented to estimate the joint velocities of a biped robot, in which an H/sub /spl infin// approach and variable structure control (VSC) are embedded to attenuate the effect of external disturbances and parametric uncertainties. After the construction of the FNN nonlinear observer, a quadratic stabilization FNN controller is developed with a robust hybrid control scheme. As the employment of a quadratic stability approach, not only does it afford the possibility of trading off the design between FNN, H/sub /spl infin// optimal control, and VSC, but conservative estimation of the FNN reconstruction error bound is also avoided by considering the system matrix uncertainty separately. It is shown that all signals in the closed-loop control system are bounded.

  1. Implementation of Steiner point of fuzzy set.

    Science.gov (United States)

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

    This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

  2. A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis.

    Science.gov (United States)

    Xiao, Fuyuan

    2017-10-31

    The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of such applications, and the Dempster-Shafer evidence theory is employed to improve the system performance; whereas, it may generate a counter-intuitive result when the pieces of evidence highly conflict with each other. To handle this problem, a novel multi-sensor data fusion approach on the basis of the distance of evidence, belief entropy and fuzzy preference relation analysis is proposed. A function of evidence distance is first leveraged to measure the conflict degree among the pieces of evidence; thus, the support degree can be obtained to represent the reliability of the evidence. Next, the uncertainty of each piece of evidence is measured by means of the belief entropy. Based on the quantitative uncertainty measured above, the fuzzy preference relations are applied to represent the relative credibility preference of the evidence. Afterwards, the support degree of each piece of evidence is adjusted by taking advantage of the relative credibility preference of the evidence that can be utilized to generate an appropriate weight with respect to each piece of evidence. Finally, the modified weights of the evidence are adopted to adjust the bodies of the evidence in the advance of utilizing Dempster's combination rule. A numerical example and a practical application in fault diagnosis are used as illustrations to demonstrate that the proposal is reasonable and efficient in the management of conflict and fault diagnosis.

  3. A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2017-10-01

    Full Text Available The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of such applications, and the Dempster–Shafer evidence theory is employed to improve the system performance; whereas, it may generate a counter-intuitive result when the pieces of evidence highly conflict with each other. To handle this problem, a novel multi-sensor data fusion approach on the basis of the distance of evidence, belief entropy and fuzzy preference relation analysis is proposed. A function of evidence distance is first leveraged to measure the conflict degree among the pieces of evidence; thus, the support degree can be obtained to represent the reliability of the evidence. Next, the uncertainty of each piece of evidence is measured by means of the belief entropy. Based on the quantitative uncertainty measured above, the fuzzy preference relations are applied to represent the relative credibility preference of the evidence. Afterwards, the support degree of each piece of evidence is adjusted by taking advantage of the relative credibility preference of the evidence that can be utilized to generate an appropriate weight with respect to each piece of evidence. Finally, the modified weights of the evidence are adopted to adjust the bodies of the evidence in the advance of utilizing Dempster’s combination rule. A numerical example and a practical application in fault diagnosis are used as illustrations to demonstrate that the proposal is reasonable and efficient in the management of conflict and fault diagnosis.

  4. Fuzzy logic

    CERN Document Server

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  5. Fuzzy Languages

    Science.gov (United States)

    Rahonis, George

    The theory of fuzzy recognizable languages over bounded distributive lattices is presented as a paradigm of recognizable formal power series. Due to the idempotency properties of bounded distributive lattices, the equality of fuzzy recognizable languages is decidable, the determinization of multi-valued automata is effective, and a pumping lemma exists. Fuzzy recognizable languages over finite and infinite words are expressively equivalent to sentences of the multi-valued monadic second-order logic. Fuzzy recognizability over bounded ℓ-monoids and residuated lattices is briefly reported. The chapter concludes with two applications of fuzzy recognizable languages to real world problems in medicine.

  6. Fuzzy Cores and Fuzzy Balancedness

    NARCIS (Netherlands)

    van Gulick, G.; Norde, H.W.

    2011-01-01

    We study the relation between the fuzzy core and balancedness for fuzzy games. For regular games, this relation has been studied by Bondareva (1963) and Shapley (1967). First, we gain insight in this relation when we analyse situations where the fuzzy game is continuous. Our main result shows that

  7. Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

    Science.gov (United States)

    Das, Arpita; Bhattacharya, Mahua

    2011-01-01

    In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.

  8. Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network

    DEFF Research Database (Denmark)

    Govindan, Kannan; Darbari, Jyoti Dhingra; Agarwal, Vernika

    2017-01-01

    into the decision making process by selecting environmentally responsible suppliers to procure components based on sustainable criteria, choosing appropriate recovery options for end-of-use (EOU) inkjet printers, and planning an efficient transportation network design for reducing the carbon emission...... activities. A weighted fuzzy mathematical programming approach is utilised for generating a fuzzy, properly efficient solution as the desired compromised solution for the CLSC network problem configuration. The relevance of the model is justified using a real data set derived from a case study of the firm...... with higher sustainable performance and vehicles with lesser emission rate could substantially enhance firm's sustainable image and result in higher profits in the future....

  9. Constructing the Indicators of Assessing Human Vulnerability to Industrial Chemical Accidents: A Consensus-based Fuzzy Delphi and Fuzzy AHP Approach.

    Science.gov (United States)

    Fatemi, Farin; Ardalan, Ali; Aguirre, Benigno; Mansouri, Nabiollah; Mohammadfam, Iraj

    2017-04-10

    Industrial chemical accidents have been increased in developing countries. Assessing the human vulnerability in the residents of industrial areas is necessary for reducing the injuries and causalities of chemical hazards. The aim of this study was to explore the key indicators for the assessment of human vulnerability in the residents living near chemical installations. The indicators were established in the present study based on the Fuzzy Delphi method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP). The reliability of FDM and FAHP was calculated. The indicators of human vulnerability were explored in two sets of social and physical domains. Thirty-five relevant experts participated in this study during March-July 2015. According to experts, the top three indicators of human vulnerability according to the FDM and FAHP were vulnerable groups, population density, and awareness. Detailed sub-vulnerable groups and awareness were developed based on age, chronic or severe diseases, disability, first responders, and residents, respectively. Each indicator and sub-indicator was weighted and ranked and had an acceptable consistency ratio. The importance of social vulnerability indicators are about 7 times more than physical vulnerability indicators. Among the extracted indicators, vulnerable groups had the highest weight and the greatest impact on human vulnerability. however, further research is needed to investigate the applicability of established indicators and generalizability of the results to other studies. Fuzzy Delphi; Fuzzy AHP; Human vulnerability; Chemical hazards.

  10. A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

    Science.gov (United States)

    Błaszczuk, Artur; Krzywański, Jarosław

    2017-03-01

    The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB) has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131-1156 K and 1.93-6.32 kg/m3, respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109-241 W/(m2K) and 111-240 W/(m2K), for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.

  11. A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

    Directory of Open Access Journals (Sweden)

    Błaszczuk Artur

    2017-03-01

    Full Text Available The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131-1156 K and 1.93-6.32 kg/m3, respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109-241 W/(m2K and 111-240 W/(m2K, for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.

  12. A new approach to analyze strategy map using an integrated BSC and FUZZY DEMATEL

    Directory of Open Access Journals (Sweden)

    Seyed Abdollah Heydariyeh

    2012-01-01

    Full Text Available Today, with ever-increasing competition in global economic conditions, the necessity of effective implementation of strategy map has become an inevitable and necessary. The strategy map represents a general and structured framework for strategic objectives and plays an important role in forming competitive advantages for organizations. It is important to find important factors influencing strategy map and prioritize them based on suitable factors. In this paper, we propose an integration of BSC and Fuzzy DEMATEL technique to rank different items influencing strategy of a production plan. The proposed technique is implemented for real-world case study of glass production.

  13. An efficient Neuro-Fuzzy approach to nuclear power plant transient identification

    International Nuclear Information System (INIS)

    Gomes da Costa, Rafael; Abreu Mol, Antonio Carlos de; Carvalho, Paulo Victor R. de; Lapa, Celso Marcelo Franklin

    2011-01-01

    Highlights: → We investigate a Neuro-Fuzzy modeling tool use for able transient identification. → The prelusive transient type identification is done by an artificial neural network. → After, the fuzzy-logic system analyzes the results emitting reliability degree of it. → The research support was made in a PWR simulator at the Brazilian Nuclear Engineering Institute. → The results show the potential to help operators' decisions in a nuclear power plant. - Abstract: Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the 'don't know' as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute (IEN

  14. Intuitionistic fuzzy proximity spaces

    OpenAIRE

    Eun Pyo Lee; Seok Jong Lee

    2004-01-01

    We introduce the concept of the intuitionistic fuzzy proximity as a generalization of fuzzy proximity, and investigate its properties. Also we investigate the relationship among intuitionistic fuzzy proximity and fuzzy proximity, and intuitionistic fuzzy topology.

  15. Risk management in medical product development process using traditional FMEA and fuzzy linguistic approach: a case study

    Science.gov (United States)

    Kirkire, Milind Shrikant; Rane, Santosh B.; Jadhav, Jagdish Rajaram

    2015-12-01

    Medical product development (MPD) process is highly multidisciplinary in nature, which increases the complexity and the associated risks. Managing the risks during MPD process is very crucial. The objective of this research is to explore risks during MPD in a dental product manufacturing company and propose a model for risk mitigation during MPD process to minimize failure events. A case study approach is employed. The existing MPD process is mapped with five phases of the customized phase gate process. The activities during each phase of development and risks associated with each activity are identified and categorized based on the source of occurrence. The risks are analyzed using traditional Failure mode and effect analysis (FMEA) and fuzzy FMEA. The results of two methods when compared show that fuzzy approach avoids the duplication of RPNs and helps more to convert cognition of experts into information to get values of risk factors. The critical, moderate, low level and negligible risks are identified based on criticality; risk treatments and mitigation model are proposed. During initial phases of MPD, the risks are less severe, but as the process progresses the severity of risks goes on increasing. The MPD process should be critically designed and simulated to minimize the number of risk events and their severity. To successfully develop the products/devices within the manufacturing companies, the process risk management is very essential. A systematic approach to manage risks during MPD process will lead to the development of medical products with expected quality and reliability. This is the first research of its kind having focus on MPD process risks and its management. The methodology adopted in this paper will help the developers, managers and researchers to have a competitive edge over the other companies by managing the risks during the development process.

  16. Fuzzy data analysis

    CERN Document Server

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  17. Multi-attribute Reverse Auction Design Based on Fuzzy Data Envelopment Analysis Approach

    Directory of Open Access Journals (Sweden)

    Deyan Chen

    2017-08-01

    Full Text Available Multi-attribute reverse auction is widely used for the procurements of enterprises or governments. To overcome the difficulty of identifying bidding attribute weight and score function of the buyer, the multi-round auction and bidding models with multiple winners are established based on fuzzy data envelopment analysis. The winner determination model of the buyer considers the integrated input-output efficiency of k winners. The bidding strategy of seller is divided into two parts: the first one estimates the weight of the ideal supplier that is thought to be the buyer’s preference; the second one is to calculate the weight of the test supplier which reflects the change trend of current weights and the seller’s weakness. The final predicted weight is the weighted sum of both. On the basis of known weight, the test supplier can improve his efficiency to increase the winning chance in the next round auction. Our models comprise crisp numbers and fuzzy numbers. Finally, a numerical example verifies the validity of the proposed models.

  18. Analytical and simulation approach to managing economic entities under fuzzy conditions

    Directory of Open Access Journals (Sweden)

    А.О. Оvezgeldyyev

    2015-12-01

    Full Text Available The factors that comprehensively characterize modern wholesale market are showed. The authors analyze the problems of real process modeling of business effective management of wholesale trade enterprises which operate in large quantities of goods in a wide range and under conditions of inaccurate and insufficient information and also when a market situation cannot be well predicted. These models are characterized by fuzzy decision-making processes. The mathematical model based on the theory of fuzzy sets, has been constructed to find areas of efficient business of wholesale trade under reformed economy, i.e. under conditions of large-scale decline in output, unpredictable price increases in related industries, rapid growth in the share of imported products and under conditions of enhanced financial differentiation between enterprises. The present business model of wholesale trade enterprises allows us to determine: - An optimal set of dependent consumers, i.e. those for which this wholesale company is practically the only supplier; - Set of competitors such as wholesale trade enterprises which also supply their products to the same customers as the company we investigate; - A set of consumers who practically do not use the services of the investigated company.

  19. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    International Nuclear Information System (INIS)

    Kucukali, Serhat; Baris, Kemal

    2010-01-01

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

  20. Gist Representations and Communication of Risks about HIV-AIDS: A Fuzzy-Trace Theory Approach.

    Science.gov (United States)

    Wilhelms, Evan A; Reyna, Valerie F; Brust-Renck, Priscila; Weldon, Rebecca B; Corbin, Jonathan C

    2015-01-01

    As predicted by fuzzy-trace theory, people with a range of training—from untrained adolescents to expert physicians—are susceptible to biases and errors in judgment and perception of HIV-AIDS risk. To explain why this occurs, we introduce fuzzy-trace theory as a theoretical perspective that describes these errors to be a function of knowledge deficits, gist-based representation of risk categories, retrieval failure for risk knowledge, and processing interference (e.g., base-rate neglect) in combining risk estimates. These principles explain how people perceive HIV-AIDS risk and why they take risks with potentially lethal outcomes, often despite rote (verbatim) knowledge.For example, people inappropriately generalize the wrong gist about condoms' effectiveness against fluid-borne disease to diseases that are transferred skin-to-skin, such as HPV. We also describe how variation in processing in adolescence (e.g., more verbatim processing compared to adults) can be a route to risk-taking that explains key aspects of why many people are infected with HIV in youth, as well as how interventions that emphasize bottom-line gists communicate risks effectively.

  1. Fuzzy VIKOR approach for selection of big data analyst in procurement management

    Directory of Open Access Journals (Sweden)

    Surajit Bag

    2016-07-01

    Full Text Available Background: Big data and predictive analysis have been hailed as the fourth paradigm of science. Big data and analytics are critical to the future of business sustainability. The demand for data scientists is increasing with the dynamic nature of businesses, thus making it indispensable to manage big data, derive meaningful results and interpret management decisions. Objectives: The purpose of this study was to provide a brief conceptual review of big data and analytics and further illustrate the use of a multicriteria decision-making technique in selecting the right skilled candidate for big data and analytics in procurement management. Method: It is important for firms to select and recruit the right data analyst, both in terms of skills sets and scope of analysis. The nature of such a problem is complex and multicriteria decision-making, which deals with both qualitative and quantitative factors. In the current study, an application of the Fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR method was used to solve the big data analyst selection problem. Results: From this study, it was identified that Technical knowledge (C1, Intellectual curiosity (C4 and Business acumen (C5 are the strongest influential criteria and must be present in the candidate for the big data and analytics job. Conclusion: Fuzzy VIKOR is the perfect technique in this kind of multiple criteria decisionmaking problematic scenario. This study will assist human resource managers and procurement managers in selecting the right workforce for big data analytics.

  2. A fuzzy-rule-based approach for single frame super resolution.

    Science.gov (United States)

    Purkait, Pulak; Pal, Nikhil Ranjan; Chanda, Bhabatosh

    2014-05-01

    In this paper, a novel fuzzy rule-based prediction framework is developed for high-quality image zooming. In classical interpolation-based image zooming, resolution is increased by inserting pixels using certain interpolation techniques. Here, we propose a patch-based image zooming technique, where each low-resolution (LR) image patch is replaced by an estimated high-resolution (HR) patch. Since an LR patch can be generated from any of the many possible HR patches, it would be natural to develop rules to find different possible HR patches and then to combine them according to rule strength to get the estimated HR patch. Here, we generate a large number of LR–HR patch pairs from a collection of natural images, group them into different clusters, and then generate a fuzzy rule for each of these clusters. The rule parameters are also learned from these LR-HR patch pairs. As a result, an efficient mapping from LR patch space to HR patch space can be formulated. The performance of the proposed method is tested on different images, and is also compared with other representative as well as state-of-the-art image zooming techniques. Experimental results show that the proposed method is better than the competing methods and is capable of reconstructing thin lines, edges, fine details, and textures in the image efficiently.

  3. Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

    Directory of Open Access Journals (Sweden)

    Saeed Khalili

    2014-08-01

    Full Text Available In the past, different methods for asset depreciation have been defined but most of these procedures deal with certain parameters and inputs. The availability of certain parameters in many real world situations is difficult and sometimes impossible. The primary objective of this paper is to obtain methods for calculating depreciation where some of the defined parameters are under uncertainty. Hence, by using the fuzzy science basics, extension principle and α-cut technique, we rewrite some classic methods for calculating depreciation in fuzzy form. Then, for comparing the methods of fuzzy depreciation under uncertain conditions by using the formula of calculating the Fuzzy Present worth (FPW, the Present worth of Tax saving (PWTS of any aforementioned methods has been obtained. Finally, since the amount of tax savings achieved for each of the methods is a fuzzy number, one of the fuzzy prioritization methods is used in order to select the best depreciation technique.

  4. Prediction of ground water quality index to assess suitability for drinking purposes using fuzzy rule-based approach

    Science.gov (United States)

    Gorai, A. K.; Hasni, S. A.; Iqbal, Jawed

    2016-11-01

    Groundwater is the most important natural resource for drinking water to many people around the world, especially in rural areas where the supply of treated water is not available. Drinking water resources cannot be optimally used and sustained unless the quality of water is properly assessed. To this end, an attempt has been made to develop a suitable methodology for the assessment of drinking water quality on the basis of 11 physico-chemical parameters. The present study aims to select the fuzzy aggregation approach for estimation of the water quality index of a sample to check the suitability for drinking purposes. Based on expert's opinion and author's judgement, 11 water quality (pollutant) variables (Alkalinity, Dissolved Solids (DS), Hardness, pH, Ca, Mg, Fe, Fluoride, As, Sulphate, Nitrates) are selected for the quality assessment. The output results of proposed methodology are compared with the output obtained from widely used deterministic method (weighted arithmetic mean aggregation) for the suitability of the developed methodology.

  5. Possible use of fuzzy logic in database

    Directory of Open Access Journals (Sweden)

    Vaclav Bezdek

    2011-04-01

    Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.

  6. Neuro-fuzzy Control of Integrating Processes

    Directory of Open Access Journals (Sweden)

    Anna Vasičkaninová

    2011-11-01

    Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.

  7. Categorizing document by fuzzy C-Means and K-nearest neighbors approach

    Science.gov (United States)

    Priandini, Novita; Zaman, Badrus; Purwanti, Endah

    2017-08-01

    Increasing of technology had made categorizing documents become important. It caused by increasing of number of documents itself. Managing some documents by categorizing is one of Information Retrieval application, because it involve text mining on its process. Whereas, categorization technique could be done both Fuzzy C-Means (FCM) and K-Nearest Neighbors (KNN) method. This experiment would consolidate both methods. The aim of the experiment is increasing performance of document categorize. First, FCM is in order to clustering training documents. Second, KNN is in order to categorize testing document until the output of categorization is shown. Result of the experiment is 14 testing documents retrieve relevantly to its category. Meanwhile 6 of 20 testing documents retrieve irrelevant to its category. Result of system evaluation shows that both precision and recall are 0,7.

  8. An Offline Fuzzy Based Approach for Iris Recognition with Enhanced Feature Detection

    Science.gov (United States)

    Kodituwakku, S. R.; Fazeen, M. I. M.

    Among many biometric identification methods iris recognition is more attractive due to the unique features of the human eye [1]. There are many proposed algorithms for iris recognition. Although all these methods are based on the properties of the iris, they are subject to some limitations. In this research we attempt to develop an algorithm for iris recognition based on Fuzzy logic incorporated with not only the visible properties of the human iris but also considering the iris function. Visible features of the human iris such as pigment related features, features controlling the size of the pupil, visible rare anomalies, pigment frill and Collarette are considered [2]. This paper presents the algorithm we developed to recognize iris. A prototype system developed is also discussed.

  9. Fuzzy Similarity Measures Approach in Benchmarking Taxonomies of Threats against SMEs in Developing Economies

    DEFF Research Database (Denmark)

    Yeboah-Boateng, Ezer Osei

    2013-01-01

    in developing economies were strategically interviewed for their expert opinions on various business and security metrics. The study established that natural disasters, which are perennial in most developing economies, are the most critical cyber-threat agent, whilst social engineering is the least critical......There are various threats that militate against SMEs in developing economies. However, most SMEs fall on the conservative “TV News Effect” of most-publicized cyber-threats or incidences, with disproportionate mitigation measures. This paper endeavors to establish a taxonomy of threat agents to fill...... in the void. Various fuzzy similarity measures based on multi-attribute decision-making techniques have been employed in the evaluation. The taxonomy offers a panoramic view of cyber-threats in assessing mission-critical assets, and serves as a benchmark for initiating appropriate mitigation strategies. SMEs...

  10. Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps

    Directory of Open Access Journals (Sweden)

    Farinaz Behrooz

    2018-02-01

    Full Text Available Heating, Ventilating, and Air Conditioning (HVAC systems are the major energy-consuming devices in buildings. Nowadays, due to the high demand for HVAC system installation in buildings, designing an effective controller in order to decrease the energy consumption of the devices while meeting the thermal comfort demands in buildings are the most important goals of control designers. The purpose of this article is to investigate the different control methods for Heating, Ventilating, and Air Conditioning and Refrigeration (HVAC & R systems. The advantages and disadvantages of each control method are discussed and finally the Fuzzy Cognitive Map (FCM method is introduced as a new strategy for HVAC systems. The FCM method is an intelligent and advanced control technique to address the nonlinearity, Multiple-Input and Multiple-Output (MIMO, complexity and coupling effect features of the systems. The significance of this method and improvements by this method are compared with other methods.

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

    DEFF Research Database (Denmark)

    Awasthi, Anjali; Govindan, Kannan; Gold, Stefan

    2018-01-01

    for sustainable global supplier selection that takes sustainability risks from sub-suppliers (i.e., (1+n)th-tier suppliers) into account. Sustainability criteria (including risk concerns) were identified from the existing literature and were further narrowed with the assistance of field experts and case decision...... weights for sustainable global supplier selection, and in the second stage, fuzzy VIKOR is used to rate supplier performances against the evaluation criteria. Among five sustainability criteria (economic, quality, environment, social, and global risk), economic criteria demonstrated the greatest weight...... and global risk displayed the least weight. This result clearly shows that global risks are still not considered a major criterion for supplier selection. Further, the proposed framework may serve as a starting point for developing managerial decision-making tools to help companies more effectively address...

  12. Fuzzy linguistic model for interpolation

    International Nuclear Information System (INIS)

    Abbasbandy, S.; Adabitabar Firozja, M.

    2007-01-01

    In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method

  13. A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

    2017-07-01

    For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other

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

    Directory of Open Access Journals (Sweden)

    Junling Zhang

    2016-03-01

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

  15. Mapping Diversity of Publication Patterns in the Social Sciences and Humanities: An Approach Making Use of Fuzzy Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Frederik T. Verleysen

    2016-11-01

    Full Text Available Purpose: To present a method for systematically mapping diversity of publication patterns at the author level in the social sciences and humanities in terms of publication type, publication language and co-authorship. Design/methodology/approach: In a follow-up to the hard partitioning clustering by Verleysen and Weeren in 2016, we now propose the complementary use of fuzzy cluster analysis, making use of a membership coefficient to study gradual differences between publication styles among authors within a scholarly discipline. The analysis of the probability density function of the membership coefficient allows to assess the distribution of publication styles within and between disciplines. Findings: As an illustration we analyze 1,828 productive authors affiliated in Flanders, Belgium. Whereas a hard partitioning previously identified two broad publication styles, an international one vs. a domestic one, fuzzy analysis now shows gradual differences among authors. Internal diversity also varies across disciplines and can be explained by researchers' specialization and dissemination strategies. Research limitations: The dataset used is limited to one country for the years 2000-2011; a cognitive classification of authors may yield a different result from the affiliation-based classification used here. Practical implications: Our method is applicable to other bibliometric and research evaluation contexts, especially for the social sciences and humanities in non-Anglophone countries. Originality/value: The method proposed is a novel application of cluster analysis to the field of bibliometrics. Applied to publication patterns at the author level in the social sciences and humanities, for the first time it systematically documents intra-disciplinary diversity.

  16. A spatial fuzzy logic approach to urban multi-hazard impact assessment in Concepción, Chile.

    Science.gov (United States)

    Araya-Muñoz, Dahyann; Metzger, Marc J; Stuart, Neil; Wilson, A Meriwether W; Carvajal, Danilo

    2017-01-15

    Even though most cities are exposed to more than one hazard, local planners and decision-makers still have a limited understanding of the exposure and sensitivity to and the spatial distribution of hazards. We examine the impact of multiple hazards in the Concepción Metropolitan Area (CMA), Chile. A flexible methodology based on spatial fuzzy logic modelling was developed to explore the impact of weather-related hazards, including coastal flooding, fluvial flooding, water scarcity, heat stress, and wildfire. 32 indicators were standardised and then aggregated through a stepwise approach into a multi-hazard impact index. We find that all the municipalities in the CMA increased their level of impact between 1992 and 2002, due to a larger increase in the exposure rather than the modest decrease in sensitivity. Municipal sensitivity was driven mostly by changes in the population's age structure. Wildfires and water scarcity appeared to have the largest impact on all municipalities. Fuzzy modelling offered high flexibility in the standardisation and aggregation of indicators with diverse characteristics, while also providing a means to explore how the interaction of numerous indicators influenced the index. The resulting maps can help identify indicators, components, and hazards or combinations of hazards that most influence the impact on municipalities. The results can be used to improve and promote dialogue among policy-makers and stakeholders regarding prioritisation of resources for urban development in ways that can also reduce exposure and sensitivity and lower vulnerability to climate change. The methods presented can be adapted to other cities. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Captive power plant selection for pakistan cement industry in perspective of current energy crises: a fuzzy-ahp approach

    International Nuclear Information System (INIS)

    Ali, H.M.; Sultan, A.; Rana, B.B.

    2017-01-01

    Based on the prevailing energy crisis, it is reasonable for the Cement industry of Pakistan to look for alternate sources of electricity generation. The decision of selecting a CPP (Captive Power Plant) depends on a broad variety of parameters which may be conflicting to each other. A comparative evaluation of these CPP's should be helpful for industry, particularly if the applied methodology can handle with the real world ambiguities and imprecisions associated with the data pools and expert opinions. This paper utilizes an F-AHP (Fuzzy Analytical Hierarchy Process) based multi-attribute framework to prioritize the affecting parameters and assign rankings to the CPP alternatives. The CPP's recommended by experts for this study are RDF-CPP (Refused Derived Fuel CPP), CF-CPP (Coal Fired CPP) and WHR-CPP (Waste Heat Recovery CPP). The factors affecting the decision of selecting the optimum CPP are prioritized by the experts using our F-AHP approach. Real world quantitative data is extracted from different online resources and financial reports of cement companies in Pakistan. The F-AHP model is flexible enough to deal with a variety of inputs including qualitative scales, crisp values and standard fuzzy numbers. The model is solved and a sensitivity analysis is performed in respective software. This study shows that non-conventional CPPs are highly demanded for cement industry in Pakistan and while selecting these CPPs, management gives high priority to factors like 'automation' and 'environment' whereas associated i nitial cost i s not given much weight in decision making. In concluding ranking list, WHR-CPP is at the top and CF-CPP is at the bottom. This study may facilitate decision makers of cement industry in Pakistan and international CPP manufacturers alike in their forthcoming strategic decisions. (author)

  18. A fuzzy rule-based approach for characterization of mammogram masses into BI-RADS shape categories.

    Science.gov (United States)

    Vadivel, A; Surendiran, B

    2013-05-01

    We present new geometric shape and margin features for classifying mammogram mass lesions into BI-RADS shape categories: round, oval, lobular and irregular. According to Breast Imaging Reporting and Data System (BIRADS), masses can be differentiated using its shape, size and density, which is how radiologist visualizes the mammograms. Measuring regular and irregular shapes mathematically is found to be a difficult task, since there is no single measure available to differentiate various shapes. It is known that for mammograms, shape features are superior to Haralick and wavelet based features. Various geometrical shape and margin features have been introduced based on maximum and minimum radius of mass to classify the morphology of masses. These geometric features are found to be good in discriminating regular shapes from irregular shapes. In this paper, each mass is described by shape feature vector consists of 17 shape and margin properties. The masses are classified into 4 categories such as round, oval, lobular and irregular. Classifying masses into 4 categories is a very difficult task compared to classifying masses as benign, malignant or normal vs. abnormal. Only shape and margin characteristics can be used to discriminate these 4 categories effectively. Experiments have been conducted on mammogram images from the Digital Database for Screening Mammography (DDSM) and classified using C5.0 decision tree classifier. Total of 224 DDSM mammogram masses are considered for experiment. The C5.0 decision tree algorithm is used to generate simple rules, which can be easily implemented and used in fuzzy inference system as if…then…else statements. The rules are used to construct the generalized fuzzy membership function for classifying the masses as round, oval, lobular or irregular. Proposed approach is twice effective than existing Beamlet based features for classifying the mass as round, oval, lobular or irregular. Copyright © 2013 Elsevier Ltd. All rights

  19. Relational Demonic Fuzzy Refinement

    Directory of Open Access Journals (Sweden)

    Fairouz Tchier

    2014-01-01

    Full Text Available We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join (⊔fuz, fuzzy demonic meet (⊓fuz, and fuzzy demonic composition (□fuz. Our definitions and properties are illustrated by some examples using mathematica software (fuzzy logic.

  20. Fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections

    OpenAIRE

    Hong, Liang

    2015-01-01

    Fuzzy ordered linear spaces, Riesz spaces, fuzzy Archimedean spaces and $\\sigma$-complete fuzzy Riesz spaces were defined and studied in several works. Following the efforts along this line, we define fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections and establish their fundamental properties.