| 基因变异的群智能优化算法研究 |
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| 引用本文： | 崔明义,张新祥,苏白云. 基因变异的群智能优化算法研究[J]. 计算机工程与应用, 2011, 47(4): 39-41. DOI: 10.3778/j.issn.1002-8331.2011.04.011 |
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| 作者姓名： | 崔明义 张新祥 苏白云 |
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| 作者单位： | 河南财经学院 信息学院，郑州 450002 |
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| 基金项目： | 河南省基础与前沿技术研究计划(No.082300410100) |
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| 摘 要： | 粒子群优化（Particle Swarm Optimization，PSO）是一种重要的群智能（Swarm Intelligence，SI）方法。早期收敛和较低的局部搜索能力是PSO的不足。提出一种新颖的基因变异PSO（Gene Mutation PSO，GMPSO），依据概率使粒子的分量发生变异，并做了大量的实验。研究和实验的结果表明，该方法可显著改变PSO的性能，在理论上是可靠的，技术上是可行的。
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| 关 键 词： | 群智能 粒子群优化 基因变异 |
| 收稿时间： | 2009-05-05 |
| 修稿时间： | 2009-6-25 |
Research on swarm intelligence optimization based on gene mutation |
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| CUI Mingyi,ZHANG Xinxiang,SU Baiyun. Research on swarm intelligence optimization based on gene mutation[J]. Computer Engineering and Applications, 2011, 47(4): 39-41. DOI: 10.3778/j.issn.1002-8331.2011.04.011 |
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| Authors: | CUI Mingyi ZHANG Xinxiang SU Baiyun |
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| Affiliation: | School of Information，Henan University of Finance & Economics，Zhengzhou 450002，China |
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| Abstract: | Particle Swarm Optimization(PSO) is one of important Swarm Intelligence(SI) methods.The premature convergence and lower local search performance are drawbacks of PSO.This paper proposes a novel Gene Mutation PSO(GMPSO),some components of particles mutate according to the probability,a lot of experiments are taken.The results of the research and experiments indicate that the method can obviously improve the performance of PSO,it is credible in theory and feasible in technique. |
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| Keywords: | swarm intelligence particle swarm optimization gene mutation
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