Fuzzy Logic with Engineering Applications

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John Wiley & Sons, Aug 16, 2004 - Technology & Engineering - 628 pages
7 Reviews
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.

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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).


Introduction I
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
Miscellaneous Topics
Belief Plausibility Probability
Appendix A Axiomatic Differences between Fuzzy Set Theory
Index of Examples and Problems by Discipline

Rulebase Reduction Methods

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About the author (2004)

Timothy J. Ross is Professor and Regents’ Lecturer of Civil Engineering at the University of New Mexico. He received his PhD degree in Civil Engineering from Stanford University, his MS from Rice University, and his BS from Washington State University. Professor Ross has held previous positions as Senior Research Structural Engineer, Air Force Weapons Laboratory, from 1978 to 1986; and Vulnerability Engineer, Defense Intelligence Agency, from 1973 to 1978. Professor Ross has authored more than 120 publications and has been active in the research and teaching of fuzzy logic since 1983. He is the founding Co-Editor-in-Chief of the International Journal of Intelligent and Fuzzy Systems and the co-editor of Fuzzy Logic and Control: Software and Hardware Applications, and most recently co-editor of Fuzzy Logic and Probability Applications: Bridging the Gap. Professor Ross is a Fellow of the American Society of Civil Engineers. He consults for industry and such institutions as Sandia National Laboratory and the National Technological University, and is a current Faculty Affiliate with the Los Alamos National Laboratory. He was recently honored with a Senior Fulbright Fellowship for his sabbatical study at the University of Calgary, Alberta, Canada.

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