Fuzzy Logic: With Engineering Applications

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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. This fully updated new edition has 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.

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Timothy J. Ross is Professorand 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. Table of Contents Preface to the Second Edition Introduction Classical Sets and FuzzySets Classical Relations and Fuzzy Relations Properties of Membership Functions, Fuzzification, and Defuzzification Logic and Fuzzy Systems Development of Membership Functions Automated Methods for Fuzzy Systems Fuzzy Systems Simulation Rule-base Reduction Methods Decision Making with Fuzzy Information Fuzzy Classification and Pattern Recognition Fuzzy Arithmetic and the Extension Principle Fuzzy Control Systems Miscellaneous Topics Monotone Measures: Belief, Plausibility, Probability, and Possibility Appendix A: Axiomatic Differences between Fuzzy Set Theory and Probability Theory Appendix B: Answers to Selected Problems Index of Examples and Problems by Discipline Index