Particle Swarm Optimization for Complex Nonlinear Optimization Problems

被引：4

作者：

Alexandridis, Alex ^{[1
]}

Famelis, Ioannis Th. ^{[1
]}

Tsitouras, Charalambos ^{[2
]}

机构：

[1] Technol Educ Inst Athens, Dept Elect Engn, GR-12210 Aigaleo, Greece

[2] Technol Educ Inst Sterea Hellas, Dept Automat Engn, Psahna Campus, GR-34400 Lamia, Greece

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2015 (ICNAAM-2015) | 2016年 / 1738卷

关键词：

Computational Intelligence; Evolutionary Computation; Particle Swarm Optimization; Runge-Kutta; NEURAL-NETWORKS;

D O I：

10.1063/1.4952356

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This work presents the application of a technique belonging to evolutionary computation, namely particle swarm optimization (PSO), to complex nonlinear optimization problems. To be more specific, a PSO optimizer is setup and applied to the derivation of Runge-Kutta pairs for the numerical solution of initial value problems. The effect of critical PSO operational parameters on the performance of the proposed scheme is thoroughly investigated.

引用

页数：4

共 6 条

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[3]

Engelbrecht A.P, 2007, Computational Intelligence an Introduction, Vsecond

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PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014), 2015, 1648

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