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
Link To Document :
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