Title :
Wavelet Neural Network Based on Modified PSO and Its Application in Pattern Recognition
Author :
Ying, Liu ; Jie, Liu ; Bing, Yan ; Hongwei, Mao ; Hongxia, Pan ; Yan, Zhang
Author_Institution :
Tianjin Key Lab. of High Speed Cutting & Precision Machining, Tianjin Univ. of Technol. & Educ., Tianjin, China
Abstract :
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.
Keywords :
image classification; learning (artificial intelligence); particle swarm optimisation; wavelet transforms; condition monitoring; fault diagnosis; iris classification experiment; modified particle swarm optimization compound model; pattern recognition; wavelet neural-network training method; Condition monitoring; Fault diagnosis; Intelligent networks; Intelligent systems; Laboratories; Neural networks; Particle swarm optimization; Pattern recognition; Stochastic processes; Wavelet analysis;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.419
