A GSO Algorithm based on Adaptive Step Size

被引：0
|
作者：
Cheng, Wen-Juan [1 ]
Tang, Shi-Xiang [1 ]
机构：
[1] Hefei Univ Technol, Sch Comp & Informat, Hefei, Anhui, Peoples R China
来源：
2016 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SECURITY (CSIS 2016) | 2016年
关键词：
Artificial GSO; FA; Position Mechanism; Step Factor; Adaptive;
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：
Affected by slow convergence in the early period for solving optimized solution of problem and unstable convergence in the later period, the artificial Glowworm Swarm Optimization (GSO) algorithm cannot acquire higher solution precision. To deal with this problem, this paper puts forward a improved GSO, it introduces step factor which can adaptively adjust step size in GSO. The experimental results show that the improved GSO algorithm has faster convergence and higher solution precision.
引用
收藏
页码：470 / 474
页数：5
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