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Fuzzy sets, decision making, and expert systems
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This book discusses the Logic of Decisions, Behavioral Decision Theory, and Decision Technology, as well as an Interactive Decision Support System for Fuzzy and Semi-fuzzy Multi-Objective Problems.Abstract:
1 Introduction.- The Logic of Decisions, Behavioral Decision Theory, and Decision Technology.- Optimization, Outranking, Evaluation.- Basics of Fuzzy Set Theory.- 2 Individual Decision Making in Fuzzy Environments.- Symmetrical Models.- Nonsymmetrical Models.- Fuzzy Utilities.- 3 Multi-Person Decision Making in Fuzzy Environments.- Basic Models.- Fuzzy Games.- Fuzzy Team Theory.- Fuzzy Group Decision Making.- 4 Fuzzy Mathematical Programming.- Fuzzy Linear and Nonlinear Programming.- Fuzzy Multi-Stage Programming.- 5 Multi-Criteria Decision Making in Ill-Structured Situations.- Fuzzy Multi-Criteria Programming.- Multi-Attribute Decision Making (MADM).- Fuzzy Outranking.- 6 Operators and Membership Functions in Decision Models.- Axiomatic, Pragmatic, and Empirical Justification.- The Measurement of Membership Functions.- Selecting Appropriate Operators in Decision Models.- 7 Decision Support Systems.- Knowledge-Based vs. Data-Based Systems.- Linguistic Variables, Fuzzy Logic, Approximate Reasoning.- An Interactive Decision Support System for Fuzzy and Semi-fuzzy Multi-Objective Problems.- Expert Systems and Fuzzy Sets.read more
Citations
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Book ChapterDOI
Fuzzifying clustering algorithms: the case study of majorclust
TL;DR: A fuzzy version of the MajorClust algorithm is introduced, which assigns documents to more than one category by taking into account a membership function for both, edges and nodes of the corresponding underlying graph.
Journal ArticleDOI
Airfoil–slat arrangement model design for wind turbines in fuzzy environment
TL;DR: The computational results reveal that the proposed methodology for performance optimization is more effective than other methods to obtain high-performance value of the C L / C D .
Journal ArticleDOI
A fuzzy decision support system for selecting the optimal scheduling rule in robotic flexible assembly cells
TL;DR: In this article, a fuzzy decision support system is implemented using the Matlab fuzzy toolbox and six common scheduling rules are considered, and three independent objectives, namely, the minimising of makespan (Cmax), total tardiness (TD) and percentage of tardy jobs (%T) are measured.
Journal ArticleDOI
Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.
TL;DR: This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model and informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment.