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In view of the defect of particle swarm optimization(PSO) which easily gets into partial extremum, the paper puts out an improved particle swarm optimization(IPSO), and applies the algorithm to the selecting of parameter of RBF neural network pit function. The algorithm searches the parameter vector which has the best fitness in the whole space, according to coding mode, iterative formula, fitness...
The training procedures of RBF neural network are faster than BP neural network and it has the global optimal ability. However, a key problem by using the RBF neural network approach is about how to choose the optimal the parameters of RBF neural network. Particle swarm optimization is introduced to select the parameters of RBF neural network. In the paper, particle swarm optimization and RBF neural...
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