Study of Fault Classification Based on PSO Wavelet Neural Network
In this paper, a novel studying-training algorithm of wavelet neural-network based on particle swarm optimization (PSO) was presented. Then it was compared with the traditional gradient descent algorithm by the fault classification experiment. The simulation result get a conclusion that the wavelet neural-network trained by PSO not only reduces the iterations, but also get the better convergence precision. It is further indicated that PSO algorithm is fit to train the wavelet neural-network and the optimized network has good signal classification ability.
H. X. Pan and J. Y. Huang, "Study of Fault Classification Based on PSO Wavelet Neural Network", Applied Mechanics and Materials, Vols. 52-54, pp. 476-481, 2011