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Advanced Fuzzy Logic Approaches in Engineering Science最新文献

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Multi-Criteria Decision-Making Approach Based on Moderator Intuitionistic Fuzzy Hybrid Aggregation Operators 基于调节直觉模糊混合聚合算子的多准则决策方法
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH011
B. Joshi, Akhilesh Singh
{"title":"Multi-Criteria Decision-Making Approach Based on Moderator Intuitionistic Fuzzy Hybrid Aggregation Operators","authors":"B. Joshi, Akhilesh Singh","doi":"10.4018/978-1-5225-5709-8.CH011","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH011","url":null,"abstract":"It has been seen in literature that the notion of intuitionistic fuzzy sets (IFSs) is very powerful tool to deal with real life problems under the environment of uncertainty. This notion of IFSs favours the intermingling of the uncertainty index in membership functions. The uncertainty index is basically generated from a lot of parameters such as lack of awareness, historical information, situation, short of standard terminologies, etc. Hence, the uncertainty index appended finding the membership grade under IFSs needs additional enhancement. Then, the concept of a moderator intuitionistic fuzzy set (MIFS) is defined by adding a parameter in the IFSs environment to make the uncertain behaviour more accurate. In this chapter, some new moderator intuitionistic fuzzy hybrid aggregation operators are presented on the basis of averaging and geometric point of views to aggregate moderator intuitionistic fuzzy information. Then, a multi-criteria decision-making (MCDM) approach is provided and successfully implemented to real-life problems of candidate selection.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123418869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Assessing Water Quality in Payments for Environmental Services 在支付环境服务费用时评估水质
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH001
Alexandre R. Choupina, E. T. Pereira, F. L. Ribeiro, M. T. Mizukoshi
{"title":"Assessing Water Quality in Payments for Environmental Services","authors":"Alexandre R. Choupina, E. T. Pereira, F. L. Ribeiro, M. T. Mizukoshi","doi":"10.4018/978-1-5225-5709-8.CH001","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH001","url":null,"abstract":"The strategy of payment for environmental services (PES) has been increasingly present in current environmental policies, due to the acknowledgment that new mechanisms are needed to stimulate the conservation and maintenance of life-supporting services, such as the services of water provision to populations and to agricultural purposes. Nevertheless, some difficulties related to the lack of consistent methodologies to analyze the efficiency and water quality are verified. The chapter applies a methodology based in an adaptive neutral fuzzy inference system (ANFIS) approach to assess water quality. With this purpose, a water quality index is developed through a fuzzy reasoning. The relative importance of water quality indicators involved in the fuzzy inference process is modeled using a multi-attribute decision-aiding method. In recent years, fuzzy-logic-based methods have demonstrated to be appropriate to address uncertainty and subjectivity in environmental problems.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130615703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fuzzy Optimization and Decision Making 模糊优化与决策
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH014
D. Bisht, P. Srivastava
{"title":"Fuzzy Optimization and Decision Making","authors":"D. Bisht, P. Srivastava","doi":"10.4018/978-1-5225-5709-8.CH014","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH014","url":null,"abstract":"Selection of the best out of several strategies is always a difficult task. Fuzzy criteria allow a better approach to deal with such situations. Fuzzy optimization is one of the best tools in decision making. This chapter covers the concept of fuzziness, fuzzy sets, fuzzy membership and the features of membership functions. Also is described is the classification of fuzzy optimization. Then, decision making and various models for decision making under fuzzy environments are discussed. Standard examples of fuzzy optimization-based decision-making are included to describe the recent trends. This chapter may help researchers to explore different aspects of fuzzy optimization in decision-making.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115167948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making 直觉模糊集的新爱因斯坦混合聚合算子及其在多准则决策中的应用
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.ch012
B. Joshi, Abhay Kumar
{"title":"New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making","authors":"B. Joshi, Abhay Kumar","doi":"10.4018/978-1-5225-5709-8.ch012","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.ch012","url":null,"abstract":"The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121654065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Fuzzy Parallel Machine Scheduling Problem Under Fuzzy Job Deterioration and Learning Effects With Fuzzy Processing Times 模糊作业劣化及学习效应下的模糊并行机调度问题
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH003
O. A. Arık, M. Toksari
{"title":"Fuzzy Parallel Machine Scheduling Problem Under Fuzzy Job Deterioration and Learning Effects With Fuzzy Processing Times","authors":"O. A. Arık, M. Toksari","doi":"10.4018/978-1-5225-5709-8.CH003","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH003","url":null,"abstract":"This chapter presents a mixed integer non-linear programming (MINLP) model for a fuzzy parallel machine scheduling problem under fuzzy job deterioration and learning effects with fuzzy processing times in order to minimize fuzzy makespan. The uncertainty of parameters such as learning/deterioration effects and processing times in a scheduling problem makes the solution of the problem uncertain. Fuzzy sets can be used to encode uncertainty in parameters. In this chapter, possibilistic distributions of fuzzy parameters and possibilistic linear programming approaches are used in order to create a solution method for MINLP model of fuzzy parallel machine scheduling problem.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126337071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Multi-Objective Optimization of ECG Process Applying Soft Computing Techniques 应用软计算技术的心电过程多目标优化
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH004
Pritam Pain, G. Bose
{"title":"Multi-Objective Optimization of ECG Process Applying Soft Computing Techniques","authors":"Pritam Pain, G. Bose","doi":"10.4018/978-1-5225-5709-8.CH004","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH004","url":null,"abstract":"The present research work focuses on the selection of significant machining parameters depending on the nature-inspired algorithm while machining alumina-aluminum interpenetrating phase composites during electrochemical grinding. Control parameters like electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) have been considered for experimentation. The response data are initially trained and tested by using Artificial Neural Network. The contradictory responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are ensured individually by employing Firefly Algorithm. A multi-response optimization for all the responses is done initially by using the Genetic algorithm. Finally, in order to obtain a single set of parametric combination for all the output simultaneously fuzzy based Grey Relational Analysis technique is adopted. These natures driven soft computing techniques corroborates well during the parametric optimization of the electrochemical grinding process.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131948085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Fuzzy Logic for Machining Applications 模糊逻辑在加工中的应用
Advanced Fuzzy Logic Approaches in Engineering Science Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-5709-8.CH016
D. Zindani, A. Roy, Kaushik Kumar, J. Davim
{"title":"Fuzzy Logic for Machining Applications","authors":"D. Zindani, A. Roy, Kaushik Kumar, J. Davim","doi":"10.4018/978-1-5225-5709-8.CH016","DOIUrl":"https://doi.org/10.4018/978-1-5225-5709-8.CH016","url":null,"abstract":"There have been umpteen research reports on the usage of artificial intelligence (AI) strategies for modelling various machining processes. One of the well-known AI strategies is that of fuzzy logic (FL) techniques that has been used for prediction of machining performance variables for both the categories of machining processes and controls the machining process. Given the increasing trend of FL in machining, the chapter reviews the application of fuzzy logic in modelling and controlling the machining processes. The work begins with introduction section and then proceeds to discuss the importance role played by FL strategies in the traditional and modern manufacturing processes. The work summarizes some of the major applications of FL-based systems in various machining processes. Limitations, advantages, and the improvements to minimize the limitations are then discussed. The authors of the chapter hope that the review will aid all those researching in the domain of manufacturing sciences and their optimization techniques.","PeriodicalId":326058,"journal":{"name":"Advanced Fuzzy Logic Approaches in Engineering Science","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124158680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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