Advanced Meta-PSO

Christian Veenhuis
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引用次数: 4

Abstract

One issue in applying PSO is to find a good working set of parameters. The standard settings are often work sufficiently but don¿t exhaust the possibilities of PSO. This paper proposes an extended Meta-PSO approach to optimize the PSO parameters as well as the neighborhood topology for a given problem by PSO itself. It is applied to four typical benchmark functions known from literature. The good results indicate that PSO is capable of optimizing itself.
先进Meta-PSO
应用粒子群算法的一个问题是找到一个好的工作参数集。标准设置通常是足够有效的,但并没有穷尽PSO的可能性。本文提出了一种扩展的元粒子群算法,通过粒子群本身对给定问题的粒子群参数和邻域拓扑进行优化。将其应用于文献中已知的四个典型基准函数。结果表明,粒子群算法具有自我优化的能力。
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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