| 基于适应值引导的粒子群改进算法 |
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| 引用本文： | 申丹丹,石跃祥,周文杰,钟喆.基于适应值引导的粒子群改进算法[J].计算机工程与应用,2015,51(14):63-66. |
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| 作者姓名： | 申丹丹 石跃祥 周文杰 钟喆 |
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| 作者单位： | 湘潭大学 信息工程学院，湖南 湘潭 411105 |
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| 基金项目： | “十二五”国家科技支撑计划项目(No.2012BAK06B04)；湖南省“十二五”重点学科资助基金。 |
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| 摘 要： | 粒子群算法是一种智能算法，被广泛用于各领域。通过比较几类常见的粒子群算法的优劣，提出了基于适应值引导的粒子群算法，以增加粒子群的多样性，从而加快收敛速度。实验结果证明，与其他算法相比，基于适应值引导的粒子算法的收敛率与收敛速度表现最佳。
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| 关 键 词： | 粒子群算法 适应值引导 收敛 |
Improved particle swarm optimization based on fitness direc-tion |
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| SHEN Dandan,SHI Yuexiang,ZHOU Wenjie,ZHONG Zhe.Improved particle swarm optimization based on fitness direc-tion[J].Computer Engineering and Applications,2015,51(14):63-66. |
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| Authors: | SHEN Dandan SHI Yuexiang ZHOU Wenjie ZHONG Zhe |
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| Affiliation: | College of Information Engineering, Xiangtan University, Xiangtan, Hunan 411105, China |
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| Abstract: | Particle Swarm Optimization （PSO）, as a kind of intelligent algorithm, is widely applied to various fields. Through comparing with several common particle swarm optimization, this paper proposes PSO based on fitness direction, in order to increase the diversity of particle swarm, then speeds up convergence. Compared with other algorithm, experimental results show improved PSO based on fitness direction performs well on the rate of convergence and the convergence speed. |
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| Keywords: | particle swarm optimization fitness direction convergence |
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