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