Fuzzy Logic with Engineering Applications
Fuzzy logic refers to a large subject dealing with a set of methods to characterize and quantify uncertainty in engineering systems that arise from ambiguity, imprecision, fuzziness, and lack of knowledge. Fuzzy logic is a reasoning system based on a foundation of fuzzy set theory, itself an extension of classical set theory, where set membership can be partial as opposed to all or none, as in the binary features of classical logic.
Fuzzy logic is a relatively new discipline in which major advances have been made over the last decade or so with regard to theory and applications. Following on from the successful first edition, this fully updated new edition is therefore very timely and much anticipated. Concentration on the topics of fuzzy logic combined with an abundance of worked examples, chapter problems and commercial case studies is designed to help motivate a mainstream engineering audience, and the book is further strengthened by the inclusion of an online solutions manual as well as dedicated software codes.
Senior undergraduate and postgraduate students in most engineering disciplines, academics and practicing engineers, plus some working in economics, control theory, operational research etc, will all find this a valuable addition to their bookshelves.
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The answer in problem no. 5.10 & 5.11 is wrong,Plzzz rectify that.
This is a clear and comprehensive account of the mathematics of Fuzzy Logic, a branch of mathematics and logic persuasive in handling the uncertainty of language and knowledge and forming the foundation of many contemporary control systems.
Examples and exercises abound and comprehensive worked-out examples supports the text.
Together with the older introduction by Cox (The Fuzzy Systems Handbook, ISBN 9780127848105) this constitues a very comprehensive and useful introduction to fuzzy systems. (Read Cox first, though).
Classical Sets and Fuzzy Sets
Classical Relations and Fuzzy Relations
Properties of Membership Functions Fuzzification
Logic and Fuzzy Systems
Development of Membership Functions
Automated Methods for Fuzzy Systems
Fuzzy Systems Simulation
Decision Making with Fuzzy Information
Fuzzy Classification and Pattern Recognition
Fuzzy Arithmetic and the Extension Principle
Fuzzy Control Systems
Belief Plausibility Probability
Appendix A Axiomatic Differences between Fuzzy Set Theory
Rulebase Reduction Methods