Research on Improvement of Particle Swarm Optimization

被引：0
|
作者：
Chang, Chunguang [1 ]
Wu, Xi [1 ]
机构：
[1] Shenyang Jianzhu Univ, Sch Management, Shenyang 110168, Liaoning, Peoples R China
来源：
CYBER SECURITY INTELLIGENCE AND ANALYTICS | 2020年 / 928卷
基金：
中国国家自然科学基金;
关键词：
Particle swarm algorithm; Two-layer structure; Improvement; DIFFERENTIAL EVOLUTION;
D O I：
10.1007/978-3-030-15235-2_174
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Although the particle swarm optimization algorithm has simple principle, few parameters and easy implementation, the particle swarm optimization algorithm is easy to fall into local optimum on multi-mode function and the local search ability is relatively weak. In this paper, the improvement of these two defects is carried out. The particle motion formula with learning model is added, and the generation strategy of a guided vector is added to improve the particle swarm optimization algorithm. The improved algorithm has a two-layer structure, and finally the research direction is prospected.
引用
收藏
页码：1287 / 1292
页数：6
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