Fuzzy Logic with Engineering Applications

Ross, Timothy J.

ISBN 10: 0071136371 / ISBN 13: 9780071136372

Published by McGraw-Hill Education (ISE Editions), 1994

About this Item

Minimal wear to cover. Seller Inventory # 2205110058

Bibliographic Details

Title: Fuzzy Logic with Engineering Applications

Publisher: McGraw-Hill Education (ISE Editions)

Publication Date: 1994

Binding: Paperback

Condition: Interior is excellent.

About this title

Synopsis:

This text covers the fundamental theory of fuzzy logic together with simple applications taken from a wide range of engineering disciplines (electrical, mechanical, civil, computer science). Fuzzy logic explores how a computer deals with ambiguity to control innovative "smart" machines, imitating the imprecise thinking of humans. The primary focus of this book is applications in a coherent, organized format, complete with a broad cross-section of applications from such fields as expert systems, control, pattern recognition and artificial intelligence. This 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.

From the Back Cover:

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

See URL:www.wileyeurope.com/go/fuzzylogic for all online material.

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.