An Improved Artificial Fish Swarm Algorithm and Its Application

被引：6
|
作者：
Xin, Guan [1 ]
Xin, Yin Yi [1 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Informat Engn, Beijing 100083, Peoples R China
来源：
MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8 | 2012年 / 433-440卷
关键词：
artificial fish swarm algorithm; invasive weed optimization; swarm intelligence; PID parameter optimization;
D O I：
10.4028/www.scientific.net/AMR.433-440.4434
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
An improved algorithm (AFSA-IWO) was developed based on the artificial fish swarm algorithm (AFSA) and invasive weed optimization (IWO). It introduces TWO, and improves its mechanism of the competitive exclusion to meet practical application. Convergence analysis was performed with some typical benchmark test functions and comparison was made with AFSA. At the same time, it uses the AFSA-IWO to optimize the PID parameters. The results showed that the approach presented better ability in leaping over the local extremum and enhancing local exploration, and can void blind searching in the later evolution period. So it is a global optimization algorithm with good feasibility and high efficiency.
引用
收藏
页码：4434 / 4438
页数：5
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