DocumentCode
2438239
Title
Two Novel Particle Swarm Optimization Algorithm Models
Author
Song, Shengli ; Kong, Li ; Cheng, Jingjing
Author_Institution
Dept. of Comput. & Commun. Eng., Zhengzhou Univ. of Light Ind., Zhengzhou, China
Volume
2
fYear
2009
fDate
26-27 Aug. 2009
Firstpage
440
Lastpage
443
Abstract
According to the intelligent behavior of social population, two novel particle swarm algorithm optimization models are proposed by enhancing collaboration and information sharing capabilities of individuals. Benchmark function simulation results show the new algorithms, with both a better stability and a steady convergence, not only enhance the local searching efficiency and global searching performance greatly, but also have faster convergence speed and higher precision, and can avoid the premature convergence problem effectively.
Keywords
particle swarm optimisation; search problems; information sharing; particle swarm optimization algorithm; social population intelligent behavior; Collaboration; Communication industry; Convergence; Cybernetics; Intelligent systems; Man machine systems; Optimization methods; Particle swarm optimization; Stability; Stochastic processes; Algorithm; Cooperation; Model; Particle Swarm Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
Conference_Location
Hangzhou, Zhejiang
Print_ISBN
978-0-7695-3752-8
Type
conf
DOI
10.1109/IHMSC.2009.232
Filename
5335947
Link To Document