Improved artificial fish swarm algorithm based on adaptive visual and step length

doi:10.3778/j.issn.1002-8331.2009.25.011

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (25): 35-37.DOI: 10.3778/j.issn.1002-8331.2009.25.011

• 研究、探讨 • Previous Articles Next Articles

Improved artificial fish swarm algorithm based on adaptive visual and step length

LIU Yan-jun，JIANG Ming-yan

School of Information Science and Engineering，Shandong University，Jinan 250100，China

Received:2008-10-23 Revised:2009-01-05 Online:2009-09-01 Published:2009-09-01
Contact: LIU Yan-jun

自适应视野和步长的改进人工鱼群算法

刘彦君，江铭炎

山东大学信息科学与工程学院，济南 250100

通讯作者: 刘彦君

Abstract

Abstract: Based on the analysis of the Artificial Fish Swarm Algorithm（AFSA），four adaptive methods are proposed to improve its convergence speed and its optimization precision.After given more artificial intelligence，the artificial fish are able to adjust their own visual and step length，so that the parameters can be designed simply.The simulation results show that the convergence speed and the optimization precision of the improved AFSA is better than that of AFSA.

Key words: artificial fish swarm algorithm, artificial intelligence, adaptive, optimization

摘要： 在对人工鱼群算法的寻优机理进行深入的分析研究的基础上，提出了四种自适应人工鱼群算法，通过赋予人工鱼更多的智能，使每条人工鱼都能根据鱼群的状态自动地选择并适时调整自身的视野和步长，从而简化了参数设定，提高了收敛速度和寻优精度。实验结果表明，改进后的人工鱼群算法，在寻优精度、收敛速度及克服局部极值的能力方面均有提高。

关键词: 人工鱼群算法, 人工智能, 自适应, 优化

CLC Number:

TP183

LIU Yan-jun，JIANG Ming-yan. Improved artificial fish swarm algorithm based on adaptive visual and step length[J]. Computer Engineering and Applications, 2009, 45(25): 35-37.

刘彦君，江铭炎. 自适应视野和步长的改进人工鱼群算法[J]. 计算机工程与应用, 2009, 45(25): 35-37.

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Improved artificial fish swarm algorithm based on adaptive visual and step length

自适应视野和步长的改进人工鱼群算法

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