| 带飞行时间因子的改进粒子群优化算法 |
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| 引用本文： | 张学林,丁树良,胡景春,段珊.带飞行时间因子的改进粒子群优化算法[J].实验技术与管理,2011,28(5):54-57. |
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| 作者姓名： | 张学林 丁树良 胡景春 段珊 |
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| 作者单位： | 1. 江西科技职业学院电子信息工程分院,江西南昌,330200
2. 江西师范大学计算机信息工程学院,江西南昌,330027 |
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| 基金项目： | 江西省高等学校教学研究课题 |
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| 摘 要： | 对于粒子群优化算法(PSO)的研究内容涉及到许多方面。目前,针对PSO算法的研究大致可以分为算法的理论研究、算法的改进研究以及算法的应用研究。该文主要是对PSO算法的改进进行了研究,提出了一种带飞行时间因子的改进的粒子群优化算法(MPSO),并通过实验验证了MPSO优化性能较之PSO有了很大的提高。
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| 关 键 词： | PSO 飞行时间因子 MPSO |
Improvement of PSO algorithm with flying time factors |
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| Zhang Xuelin,Ding Shuliang,Hu Jingchun,Duan Shan.Improvement of PSO algorithm with flying time factors[J].Experimental Technology and Management,2011,28(5):54-57. |
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| Authors: | Zhang Xuelin Ding Shuliang Hu Jingchun Duan Shan |
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| Institution: | 1(1.Electronic and Information Engineering Branch,Jiangxi Institute of Science and Technology,Nanchang 330200,China;2.College of Computer and Information Engineering,Jiangxi Normal University,Nanchang 330027,China) |
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| Abstract: | For the research of PSO(particle swarm optimization),there are a number of institutions and individuals,and the content of the study also touched on many aspects.At present,the study of PSO algorithm can be divided into the following three: theory research,improvement research and applied research.This article mainly is to improve PSO algorithm for research and puts forward a flying time factor to the improvement of the particles of the algorithm(MPSO) and through experiments it can verify that the MPSO optimized performance is much better than that of PSO. |
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| Keywords: | PSO flying time factor MPSO |
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