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.
J. WESLEY HINES, PhD, is a research assistant professor in the Nuclear Engineering Department at the University of Tennessee.
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.