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This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.

Computer science. --- Artificial intelligence. --- Neural networks (Computer science). --- Computational intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computational Intelligence. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Natural computation --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Fuzzy systems. --- Neural networks (Computer science) --- Systems, Fuzzy --- System analysis --- Fuzzy logic --- Engineering. --- Artificial Intelligence. --- Construction --- Industrial arts --- Technology --- Neural networks (Computer science) .