A method of wavelet neural network based on particle swarm optimization algorithm

被引：0
|
作者：
Pan Hongxia [1 ]
Mao Hongwei [1 ]
Huang Jinying [1 ]
机构：
[1] N Univ China, Sch Mech Engn & Automatizat, Shanxi 030051, Taiyuan, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2007年 / 14卷
关键词：
gear-box fault; particle swarm optimization (PSO); pattern classification; wavelet neural-network;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a particle swarm optimization (PSO) algorithm is presented and it is used to optimize the parameters of wavelet neural-network, instead of the traditional gradient descent algorithms Then the PSO-trained wavelet neural-network is applied to the gear-box fault classification. it is indicated from the experimental result that the wavelet neural-network based on PSO algorithm is an effective training algorithm, and meanwhile it is also an available approach to solve the pattern classification problems.
引用
收藏
页码：935 / 939
页数：5
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