Fuzzy Logic with Engineering Applications
Timothy J. Ross(Author)
Wiley (Publisher)
Published on 25. June 2004
Software
Other digital
650 pages
978-0-470-86077-9 (ISBN)
Description
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.
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.
Reviews / Votes
"...an excellent textbook for engineering students as well as a useful resource for practicing professionals in the various engineering areas. In fact, there is no other book on the market that can compete with it for this audience." (International Journal of General Systems, June 2005)More details
Language
English
Place of publication
Hoboken
United Kingdom
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Dimensions
Height: 247 mm
Width: 173 mm
Weight
1024 gr
ISBN-13
978-0-470-86077-9 (9780470860779)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Person
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.
Content
About the Author. Preface to the Second Edition. 1. Introduction. 2. Classical Sets and Fuzzy Sets. 3. Classical Relations and Fuzzy Relations. 4. Properties of Membership Functions, Fuzzification, and Defuzzification. 5. Logic and Fuzzy Systems. 6. Development of Membership Functions. 7. Automated Methods for Fuzzy Systems. 8. Fuzzy Systems Simulation. 9. Rule-base Reduction Methods. 10. Decision Making with Fuzzy Information. 11. Fuzzy Classification and Pattern Recognition. 12. Fuzzy Arithmetic and the Extension Principle. 13. Fuzzy Control Systems. 14. Miscellaneous Topics. 15. 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.