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A novel global artificial fish swarm algorithm with improved chaotic search

被引：2
|
作者：
Xu, Ying [1 ,2 ]
Chen, Hongan [2 ]
机构：
[1] South China Univ Technol, Coll Automat, Guangzhou 510640, Guangdong, Peoples R China
[2] Wuyi Univ, Coll Informat & Engn, Jiangmen 520020, Peoples R China
来源：
MATERIALS PROCESSING TECHNOLOGY II, PTS 1-4 | 2012年 / 538-541卷
关键词：
artificial fish swarm algorithm; global optimum; chaotic search; differential evolution;
D O I：
10.4028/www.scientific.net/AMR.538-541.2594
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The artificial fish swarm algorithm, it may be trapped in local optimum in the later evolution period and its search accuracy is dependent on step length which is hard to keep balance between rapidity and accuracy. Aimed at the defects of AFSA, a novel global artificial fish swarm algorithm is proposed in this paper, in which normal chaotic search on earlier stage is modified, and a differential evolution with improved chaos search was proposed to lead artificial fish into global optimum value. The experimental results show that the proposed algorithm is not only superior to traditional one but also can make the result greater.
引用
收藏
页码：2594 / +
页数：2
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