Fuzzy And Neural Approaches in Engineering

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Lefteri H. Tsoukalas (Purdue University) Robert E. Uhrig (University of Tennessee and Oak Ridge National Laboratory)

Fuzzy And Neural Approaches in Engineering

Lefteri H. Tsoukalas (Purdue University), Robert E. Uhrig (University of Tennessee and Oak Ridge National Laboratory), Lotfi A. Zadeh (University of California, Berkeley)

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English

Wiley-Interscience
22 January 1997

Fuzzy set theory; Maths for engineers; Maths for computer scientists; Computer architecture & logic design; Neural networks & fuzzy systems

Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control

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.

By: Lefteri H. Tsoukalas (Purdue University), Robert E. Uhrig (University of Tennessee and Oak Ridge National Laboratory)
Foreword by: Lotfi A. Zadeh (University of California Berkeley)
Imprint: Wiley-Interscience
Country of Publication: United States
Dimensions: Height: 240mm, Width: 160mm, Spine: 37mm
Weight: 989g
ISBN: 9780471160038
ISBN 10: 0471160032
Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Pages: 600
Publication Date: 22 January 1997
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Introduction to Hybrid Artificial Intelligence Systems. FUZZY SYSTEMS: CONCEPTS AND FUNDAMENTALS. Foundations of Fuzzy Approaches. Fuzzy Relations. Fuzzy Numbers. Linguistic Descriptions and Their Analytical Forms. Fuzzy Control. NEURAL NETWORKS: CONCEPTS AND FUNDAMENTALS. Fundamentals of Neural Networks. Backpropagation and Related Training Algorithms. Competitive, Associative, and Other Special Neural Networks. Dynamic Systems and Neural Control. Practical Aspects of Using Neural Networks. INTEGRATED NEURAL-FUZZY TECHNOLOGY. Fuzzy Methods in Neural Networks. Fuzzy Methods in Fuzzy Systems. Selected Hybrid Neurofuzzy Applications. Dynamic Hybrid Neurofuzzy Systems. OTHER ARTIFICAL INTELLIGENCE SYSTEMS. Expert Systems in Neurofuzzy Systems. Genetic Algorithms. Epilogue. Appendix. Index.

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.