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Fuzzy Set Theory - and Its Applications
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The book updates the research agenda with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research.Abstract:
Fuzzy Set Theory - And Its Applications, Third Edition is a textbook for courses in fuzzy set theory. It can also be used as an introduction to the subject. The character of a textbook is balanced with the dynamic nature of the research in the field by including many useful references to develop a deeper understanding among interested readers. The book updates the research agenda (which has witnessed profound and startling advances since its inception some 30 years ago) with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research. All chapters have been updated. Exercises are included.read more
Citations
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Journal ArticleDOI
An Inexact Two-stage Fuzzy-stochastic Programming Model for Water Resources Management
TL;DR: The ITFSP could produce more system benefit than existing methods and deal with flexible penalty policies for better water management and utilization and comparisons with conventional two-stage stochastic programming approach are undertaken.
Journal ArticleDOI
Analyzing drivers and barriers of coordination in humanitarian supply chain management under fuzzy environment
Gaurav Kabra,A. Ramesh +1 more
TL;DR: This is the first kind of study that prioritizes the solutions to enhance coordination in HSC based on the weight of the barriers, and proposed and prioritized 15 solutions to overcome barriers to coordination and improve the competencies of humanitarian supply chain.
Book ChapterDOI
Multi-Criteria Decision Making Methods and Fuzzy Sets
TL;DR: In this chapter, crisp MADM and MODM methods are first summarized briefly and then the diffusion of the fuzzy set theory into these methods is explained.
Journal ArticleDOI
Comparative analysis of MCDM methods for the assessment of mortality in patients with acute coronary syndrome
Wojciech Sałabun,Andrzej Piegat +1 more
TL;DR: Comparison of accuracy selected MCDM methods is presented and rankings obtained by the COMET method are distinctly more accurate than those obtained by TOPSIS or AHP techniques.
Journal ArticleDOI
Fuzzy conceptual rainfall–runoff models
TL;DR: It is shown that the fuzzy logic framework enables the decision maker to gain insight about the model sensitivity and the uncertainty stemming from the elements of the CRR model.
References
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Book
Decision-making in a fuzzy environment
Richard Bellman,Lotfi A. Zadeh +1 more
TL;DR: A reverse-flow technique is described for the solution of a functional equation arising in connection with a decision process in which the termination time is defined implicitly by the condition that the process stops when the system under control enters a specified set of states in its state space.
Book ChapterDOI
A framework for representing knowledge
TL;DR: The enormous problem of the volume of background common sense knowledge required to understand even very simple natural language texts is discussed and it is suggested that networks of frames are a reasonable approach to represent such knowledge.
Journal ArticleDOI
Social Choice and Individual Values.
Leo A. Goodman,Kenneth J. Arrow +1 more
TL;DR: In this article, the authors present a destination search and find the appropriate manuals for their products, providing you with many Social Choice And Individual Values. You can find the manual you are interested in in printed form or even consider it online.
Book
Principles of Artificial Intelligence
TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Journal ArticleDOI
Fuzzy programming and linear programming with several objective functions
TL;DR: It is shown that solutions obtained by fuzzy linear programming are always efficient solutions and the consequences of using different ways of combining individual objective functions in order to determine an “optimal” compromise solution are shown.