Particle Swarm with Self-Organized Criticality

被引：0

作者：

Fernandes, Carlos M. ^{[1
,2
]}

Merelo, J. J. ^{[2
]}

Fernandez, Francisco ^{[3
]}

Rosa, Agostinho C. ^{[1
]}

机构：

[1] Univ Tecn Lisboa, Av Rovisco Pais 1,TN 6-21, P-1049001 Lisbon, Portugal

[2] Univ Granada, Dept Comp Architecture & Technol, ETSIIT, E-18071 Granada, Spain

[3] Univ Extremadura, Dept Comp Architecture & Technol, Merida, Venezuela

来源：

PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION COMPANION (GECCO'12) | 2012年

关键词：

Particle Swarm Optimization; Self-Organized Criticality; Parameter Control;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a strategy for controlling the parameters of the Particle Swarm Optimization (PSO) based on a Self-Organized Criticality (SOC) system known as the Bak-Sneppen model of co-evolution. An experimental setup compares the new algorithm with a state-of-the-art PSO with dynamic variation of the inertia weight value and perturbation of the particles' positions.

引用

页码：1397 / 1398

页数：2

共 6 条

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[2]

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[3]

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