Classical Sets and Fuzzy Sets. Basic Definitions and Terminology -- Approximate Reasoning -- Artificial Neural Networks -- Unsupervised Learning. Clustering Methods -- Fuzzy Systems -- Neuro-Fuzzy Systems -- Applications of Artificial Neural Network Based Fuzzy Inference System.
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SUMMARY OR ABSTRACT
Text of Note
The book provides an introduction to basic concepts as well as some recent advancements in fuzzy set theory, approximate reasoning, artificial neural networks and clustering methods. These methodologies create together the so-called soft computing, which is part of a computational approach to system intelligence. The book deals with an overview of fuzzy set theory, foundations for approximate reasoning principles, specific equivalence of inference results using logical conjunctive interpretations of if-then rules, supervised and unsupervised artificial neural networks, a new generalized conditional fuzzy clustering method, artificial neural networks-based fuzzy inference system with parameterized consequences in if-then rules, MATLAB(R) m-files implementation of neuro-fuzzy systems, detailed study of neuro-fuzzy systems applications.