Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Series: Adaptive and Learning Systems for Signal Processing, Communications and Control Series. Num Pages: 600 pages, Illustrations. BIC Classification: PBWX; TBJ; TJ; UYAM; UYF; UYQN. Category: (P) Professional & Vocational. Dimension: 244 x 168 x 38. Weight in Grams: 1016. . 1997. 1st Edition. Hardcover. . . . .

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Bibliographic Details

Title

Fuzzy and Neural Approaches in Engineering

Publisher

John Wiley & Sons Inc

Publication Date

1997

Language

English

ISBN 10

0471160032

ISBN 13

9780471160038

Binding

Hardcover

Edition

1st Edition

Condition

New

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About this title

Synopsis

Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. This definitive book presents the fundamentals of both technologies, and demonstrates how to combine the unique capabilities of these two technologies for the greatest advantage. Steering clear of unnecessary mathematics, the book highlights a wide range of dynamic possibilities and offers numerous examples to illuminate key concepts. It also explores the value of relating genetic algorithms and expert systems to fuzzy and neural technologies.

About the Author

LEFTERI H. TSOUKALAS, PhD, is on the faculty of the School of Nuclear Engineering at Purdue University and is an active industrial consultant and speaker. ROBERT E. UHRIG, PhD, holds a joint appointment as Distinguished Professor in the Nuclear Engineering Department at the University of Tennessee and Distinguished Scientist in the Instrumentation and Control Division at the Oak Ridge National Laboratory. He is the author of Random Noise Techniques in Nuclear Reactor Systems.

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