北华大学学报（自然科学版）2016，Vol.17Issue(2)：266-269,4.DOI:10.11713/j.issn.1009-4822.2016.02.027
一种基于拟蒙特卡罗法的骨干粒子群改进算法
An Improved BBPSO Algorithm Using Quasi-Monte Carlo
摘要
Abstract
Aimed to the classics Bare Bones PSO ( BBPSO ) was easily influenced by initialized position distribution,one initial strategy based on Quasi-Monte Carlo was proposed in this paper.New strategy enhanced the performance of BBPSO by assured randomness of the particles initialized distribution.Four numerical experiments showed the algorithm' s convergence speed and search accuracy have been improved by using the new strategy.关键词
骨干粒子群/拟蒙特卡罗法/随机初始化Key words
bare bones swarms/Quasi-Monte Carlo/random initialization分类
信息技术与安全科学引用本文复制引用
朱雅敏,薛鹏翔..一种基于拟蒙特卡罗法的骨干粒子群改进算法[J].北华大学学报（自然科学版）,2016,17(2):266-269,4.基金项目
陕西省教育厅科学研究计划专项项目(14JK1347). （14JK1347）
