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Wavelet Neural Network Based on Modified PSO and Its Application in Pattern Recognition

A modified particle swarm optimization--compound model PSO with stochastic inertia weigh is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to the Iris classification experiment. The experimental result indicates that the wavelet neural-network training method based on the modified PSO is effective. This is an available approach to solve some problems, such as the pattern recognition, condition monitoring and fault diagnosis, etc.