首页 | 本学科首页   官方微博 | 高级检索  
     

一种随机粒子群算法及应用
引用本文:李盼池,王海英,杨雨.一种随机粒子群算法及应用[J].计算机系统应用,2012,21(2):245-248,217.
作者姓名:李盼池  王海英  杨雨
作者单位:1. 东北石油大学石油与天然气工程博士后科研流动站,大庆163318;东北石油大学计算机与信息技术学院,大庆163318
2. 东北石油大学计算机与信息技术学院,大庆,163318
基金项目:基金项目:黑龙江省教育厅科学技术研究项目(115510i5)
摘    要:为提高粒子群算法的优化效率,在分析量子粒子群优化算法的基础上,提出了一种随机粒子群优化算法。该算法只有一个控制参数,搜索步长由一个随机变量的取值动态决定,通过合理设计控制参数的取值,实现对目标位置的跟踪。标准测试函数极值优化和聚类优化的实验结果表明,与量子粒子群和普通粒子群算法相比,该算法在优化能力和优化效率两方面都有改进。

关 键 词:随机粒子群优化  粒子群优化  群智能优化  仿生智能优化  算法设计
收稿时间:2011/6/11 0:00:00
修稿时间:2011/7/11 0:00:00

Random Particle Swarm Optimization Algorithm and Its Application
LI Pan-Chi,WANG Hai-Ying and YANG Yu.Random Particle Swarm Optimization Algorithm and Its Application[J].Computer Systems& Applications,2012,21(2):245-248,217.
Authors:LI Pan-Chi  WANG Hai-Ying and YANG Yu
Affiliation:(Post-Doctoral Research Center of Oil and Gas Engineering, Northeast Petroleum University, Daqing 163318, China) 2(Schnol of Computer & Information Technology, Northeast Petroleum University, Daqing 163318, China)
Abstract:To improve the efficiency of particle swarm optimization, a random particle swarm optimization algorithm is proposed on the basis of analyzing the search process of quantum particle swarm optimization lgorithm. The proposed algorithm has only a parameter, and its search step length is controlled by a random variable value. In this model, the target position can be accurately tracked by the reasonable design of the control parameter. The experimental results of standard test function extreme optimization and clustering optimization show that the proposed algorithm is superior to the quantum particle swarm optimization and the common particle swarm optimization algorithm in optimization ability and optimization efficiency.
Keywords:random particle swarm optimization  particle swarm optimization  swarm intelligent optimization  bionicintelligent optimization  algorithm design
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机系统应用》浏览原始摘要信息
点击此处可从《计算机系统应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号