模糊参数粒子群优化

2008 First International Conference on Intelligent Networks and Intelligent Systems Pub Date : 2008-11-01 DOI:10.1109/ICINIS.2008.111

P. Yadmellat, S. Salehizadeh, M. Menhaj

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引用次数: 8

摘要

本文提出了一种新的模糊调谐参数粒子群优化算法(FPPSO)，该算法明显优于标准粒子群优化算法和以往基于模糊的粒子群优化算法。使用两个具有非对称初始范围设置的基准函数来验证所提出的算法，并将其与其他称为基于模糊的粒子群算法的性能进行比较。数值结果表明，FPPSO具有较好的全局最优寻优能力和较好的收敛性能，具有很强的竞争力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fuzzy Parameter Particle Swarm Optimization

This paper proposes a new fuzzy tuned parameter particle swarm optimization (FPPSO) which remarkably outperforms the standard PSO as well as the previous fuzzy based approaches. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as fuzzy based PSO. Numerical results indicate that FPPSO is considerably competitive due to its ability to find the functions' global optimum as well as its better convergence performance..

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2008 First International Conference on Intelligent Networks and Intelligent Systems

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