Neural network as a new technology in the field of artificial intelligence, has excellent nonlinear mapping ability, with its superior performance in pattern recognition, system modeling, has been widely used in many industries, and has played a good role. This book, starting from the RBF network training algorithms, structural decomposition, structural optimization, sample selection, analyzes the methods and implementation methods how to improve neural network generalization and convergence rate, and puts forward the fast resources optimize network (FRON) algorithm, RBF network construction method (RS-RBF method) based on the rough set theory, based on multi-agent system design principle of neural network construction method (MANN method). It also introduces the implementation of the neural network in predictive control and fault diagnosis of thermal processes, combined with on-site operation and experimental data, it gave out the application examples.
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