A Modified Particle Swarm Optimization Algorithm

被引：0
|
作者：
Liu, Enhai [1 ]
Dong, Yongfeng [1 ]
Song, Jie [1 ]
Hou, Xiangdan [1 ]
Li, Nana [1 ]
机构：
[1] Hebei Univ Technol, Coll Comp Sci & Software, Tianjin 300401, Peoples R China
来源：
2008 INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND TRAINING AND 2008 INTERNATIONAL WORKSHOP ON GEOSCIENCE AND REMOTE SENSING, VOL 2, PROCEEDINGS, | 2009年
关键词：
D O I：
10.1109/ETTandGRS.2008.355
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Particle Swarm Optimization Algorithm is a kind of auto-adapted search optimization based on community. But the standard particle swarm optimization has the defects of prematurity, stagnation when applied in optimizing problems and easily leading to local minimum. A Modified Particle Swarm Optimization algorithm is proposed to improve from the initial solution and the search precision. The results show the algorithm computation precision is increased, the algorithm convergence is improved, and the local minimum phenomenon is mainly avoided. The experimental results of classic functions show that the Modified PSO is efficient and feasible.
引用
收藏
页码：666 / 669
页数：4
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