A hybrid of artificial fish swarm algorithm and particle swarm optimization for feedforward neural network training

被引：4

作者：

Chen, Huadong ^{[1
]}

Wang, Shuzong ^{[1
]}

Li, Jingxi ^{[1
]}

Li, Yunfan

机构：

[1] Naval Univ Engn, Res Inst New Weaponry Technol & Applicat, Wuhan 430033, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007) | 2007年

关键词：

artificial fish-swarm algorithm; particle swarm optimization; artificial neural networks;

D O I：

10.2991/iske.2007.174

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A hybrid of artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO) is used to training feedforward neural network. After the two algorithms are introduced respectively, the hybrid algorithm based on the two is expressed. The hybrid not only has the artificial fish behaviors of swarm and follow, but also takes advantage of the information of the particle. An experiment with a function approximation is simulated, which proves that the hybrid is more effective than AFSA and PSO.

引用

页数：1

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