Optimization for Artificial Neural Network with Adaptive Inertial Weight of Particle Swarm Optimization

被引：0
|
作者：
Park, Tae-Su [1 ]
Lee, Ju-Hong [1 ]
Choi, Bumghi [1 ]
机构：
[1] Inha Univ, Dept Comp & Informat Engn, Inchon, South Korea
来源：
PROCEEDINGS OF THE 8TH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS | 2009年
关键词：
Particle Swarm Optimization; Artificial Neural Network; Adaptive Inertial Weight;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a new method to optimize weights of Artificial Neural Network (ANN) with particle swarm optimization (PSO), also we propose a new selection strategy of inertial weight, which varies according to the training error of artificial neural network, called adaptive inertial weight. By using Adaptive inertial weight, the proposed method can search global optimal solution faster and exactly. The experimental results show that the proposed method is successfully applied to benchmark examples.
引用
收藏
页码：481 / 485
页数：5
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