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Adaptive Genetic Algorithm for Multilayer RBF Network and its Application on Real Function Approximation

With the application of adaptive genetic algorithm to the training of multi-layer RBF networks and the optimization of the hidden layer centers and width values and using regularized least squares method, weight vectors is obtained. Computer simulation shows that the precision of real function approximation by this algorithm is much higher than the precision by clustering algorithm for multi-layer RBF networks.