Computer Science ›› 2009, Vol. 36 ›› Issue (11): 193-195.
Previous Articles Next Articles
ZHENG Chun-ying,ZHENG Quan-di,WANG Xiao-dan,WANG Yu-bing
Online:
Published:
Abstract: Aiming at premature defect and poor result of Particle Swarm Optimization algorithm, a new Self-adaptive inertia factor was designed according to diversity in the population and generation number based on analysing inertia factor's effect of algorithm. And through ploughing around adjusting step factors,the Particle's ability in local searching was enhanced. Three typical function tests were given. Comparing with APSO, the result indicates the effectiveness of this improvement.
Key words: Particle swarm optimization algorithm, Inertia factor, Generation number
ZHENG Chun-ying,ZHENG Quan-di,WANG Xiao-dan,WANG Yu-bing. Self-adaptive Particle Swarm OPtimization Algorithm Based on Tentative Adjusting Step Factor[J].Computer Science, 2009, 36(11): 193-195.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: https://www.jsjkx.com/EN/
https://www.jsjkx.com/EN/Y2009/V36/I11/193
Cited