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By the simulation instance, this paper carries out a comparative research of the function approximation ability of BP network and RBF network, and analyzes the fitting accuracy and time efficiency of these two artificial neural networks when they are used to accomplish nonlinear function fitting under the specified parameters. The results show that the function approximation ability of BP network...
To avoid BP algorithm's shortcoming of falling into local minima and to take advantage of the genetic algorithm's globe optimal searching, combining genetic algorithm with BP neural network, we established the model of nonlinear function approximation based on genetic — algorithm — optimized BP neural network, analysed the toplogical structures of networks and described its learning algorithm. In...
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