DocumentCode
3300097
Title
An Improved Gaussian Dynamic Particle Swarm Optimization Algorithm
Author
Ni, Qingjian ; Xing, Hancheng
Author_Institution
Coll. of Comput. Sci. & Eng., Southeast Univ., Nanjing
Volume
1
fYear
2006
fDate
Nov. 2006
Firstpage
316
Lastpage
319
Abstract
An improved Gaussian dynamic particle swarm optimization (PSO) algorithm is proposed in this paper. In the proposed version of PSO, the original swarm of particles is initialized by canonical PSO. The time varying linear inertial weight is reintroduced to add to the position update formula. And the crazinness variable is also used in order to maintain the diversity of particle swarms. The performance of improved Gaussian dynamic PSO is demonstrated by applying it to several benchmark functions and comparing to other variants of PSO
Keywords
Gaussian processes; particle swarm optimisation; time-varying systems; Gaussian dynamic particle swarm optimization algorithm; time varying linear inertial weight; Benchmark testing; Birds; Computer science; Educational institutions; Equations; Evolutionary computation; Genetic algorithms; Marine animals; Particle swarm optimization; Space exploration;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security, 2006 International Conference on
Conference_Location
Guangzhou
Print_ISBN
1-4244-0605-6
Electronic_ISBN
1-4244-0605-6
Type
conf
DOI
10.1109/ICCIAS.2006.294146
Filename
4072099
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