This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.
Table of Contents
Foreword. Preface. Introduction to Artificial Intelligence Systems. Part I: NEURAL NETWORKS-Fundamentals of Neural Networks. Backpropagation Networks. Associative Memory. Adaptive Resonance Theory. Part II: FUZZY LOGIC-Fuzzy Set Theory. Fuzzy Systems. Part III: GENETIC ALGORITHMS-Fundamentals of Genetic Algorithms. Genetic Modelling. Part IV: HYBRID SYSTEMS-Integration of Neural Networks, Fuzzy Logic and Genetic Algorithms. Genetic Algorithm based Backpropagation Network. Fuzzy Backpropagation Network. Simplified Fuzzy ARTMAP. Fuzzy Associative Memories. Fuzzy Logic Controlled Genetic Algorithms. Word Index. Author Index.