Fuzzy Logic with Engineering Applications - Softcover

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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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Fuzzy logic is a simple phrase that actually 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.

This 15-chapter textbook remains the only major text that can be used for both undergraduate and graduate classroom instruction in this technology field. The first 8 chapters of the text cover fundamental materials useful in characterizing various forms of uncertainty and in developing the methods to quantify these uncertainties. Four chapters present specific case studies in decision making, classification and pattern recognition, control, simulation, and fuzzy arithmetic. There is one chapter on miscellaneous applications of fuzzy logic, one chapter on new rule-reduction techniques, and the final chapter presents material on other uncertainty theories with examples using evidence theory, possibility theory, and probability theory.

Key features include:

• end-of-chapter references and exercise problems
• solutions to selected exercise problems
• an accompanying online instructors' solution manual
• accompanying online software and updates
• examples of applications in most engineering disciplines: civil, chemical, mechanical, electrical, and computer science and engineering

This book will appeal to senior undergraduate and graduate students in engineering, and to graduate students in many other scientific fields. Practitioners in control theory, classification, systems integration and systems modeling and operations research application will also find this a useful text.