DocumentCode :
2305302
Title :
Gaussion Mutation Particle Swarm Optimization with Dynamic Adaptation Inertia Weight
Author :
Lili Li ; Xingshi He
Author_Institution :
Dept. of Math., Xi´an Polytech. Univ., Xi´an, China
Volume :
4
fYear :
2009
fDate :
19-21 May 2009
Firstpage :
454
Lastpage :
459
Abstract :
An improved PSO with decreasing inertia weight is proposed in this paper, which is different from the inertia weight of standard PSO. In addition, a new social component instead of the old one to make more explore and a tiny Gauss perturbation joined in the position equation to help maintain swarm diversity. Four standard test functions with asymmetric initial range settings are used to prove its validity. Experimental results verify its superiority both in convergent speed and solution precision. Conclusions are drawn in the end.
Keywords :
Gaussian processes; optimisation; Gauss perturbation; Gaussion mutation; dynamic adaptation inertia weight; particle swarm optimization; position equation; standard test functions; Cultural differences; Equations; Gaussian processes; Genetic mutations; Mathematics; Neural networks; Particle swarm optimization; Software engineering; Software standards; Testing; Gaussion mutation; Particle Swarm Optimization; inertia weight;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, 2009. WCSE '09. WRI World Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3570-8
Type :
conf
DOI :
10.1109/WCSE.2009.24
Filename :
5319596
Link To Document :
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