Paper Title:
Study of Fault Classification Based on PSO Wavelet Neural Network
  Abstract

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.

  Info
Periodical
Edited by
Zhou Mark
Pages
476-481
DOI
10.4028/www.scientific.net/AMM.52-54.476
Citation
H. X. Pan, J. Y. Huang, "Study of Fault Classification Based on PSO Wavelet Neural Network", Applied Mechanics and Materials, Vols. 52-54, pp. 476-481, 2011
Online since
March 2011
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