Hybrid quantum particle swarm optimization algorithm and its application

被引：1
|
作者：
Yukun WANG [1 ,2 ]
Xuebo CHEN [2 ]
机构：
[1] School of Chemical Engineering,University of Science and Technology Liaoning
[2] School of Electronic and Information Engineering,University of Science and Technology Liaoning
来源：
ScienceChina(InformationSciences) | 2020年 / 63卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Hybrid quantum particle swarm optimization algorithm and its application;
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：
Dear editor,Quantum-behaved particle swarm optimization(QPSO) is an evolutionary algorithm with quantum behavior. It can be used to solve optimization problems by establishing a potential well at the local attraction point to influence the location of particles [1, 2]. The algorithm offers many advantages, such as the requirement of a few parameters,simple operation, and strong convergence ability.
引用
收藏
页码：203 / 205
页数：3
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