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一种混合拓扑结构的粒子群优化算法

A New Particle Swarm Optimization with Mix Topological Structure
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摘要 为进一步提高粒子群优化算法的搜索性能,在分析不同拓扑结构对算法性能影响的基础上,针对不同拓扑结构粒子群优化算法的优缺点,提出一种混合使用全局版本和局部版本粒子群优化算法的方法,每一代粒子在速度更新时随机选择全局模型或局部模型方式进行.在典型测试函数上进行对比实验,结果验证了新算法不仅能有效地进行全局搜索,而且具有更好的收敛精度. To improve the searching performance of particle swarm optimization,bases on the analysis of the different topology effect on the performance of particle swarm optimization,this paper presents a new particle swarm optimization with mix topological structure.In each generation,the particles speed update method is randomly selected by global model or local model.The experimental results show that the new algorithm can greatly improve the global search ability and enhance the precision of convergence.
作者 黄少荣
机构地区 广东司法警官职业学院信息管理系
出处 《辽宁大学学报（自然科学版）》 CAS 2012年第2期153-156,共4页 Journal of Liaoning University：Natural Sciences Edition
基金 广东省自然科学基金项目(101754539192000000)
关键词 粒子群优化算法 混合拓扑结构 多峰函数 单峰函数 particle swarm optimization（PSO） mix topological structure unimodal function multimodal funtion
分类号 TP301 [自动化与计算机技术—计算机系统结构]
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参考文献9

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二级参考文献11

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共引文献4

辽宁大学学报（自然科学版）
2012年 第2期

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