DocumentCode
501721
Title
Individual Cognitive Parameter Setting Based on Black Stork Foraging Process
Author
Cui, Zhihua
Author_Institution
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Volume
1
fYear
2009
fDate
12-14 Aug. 2009
Firstpage
377
Lastpage
381
Abstract
Cognitive learning factor is an important parameter in particle swarm optimization algorithm(PSO). Although many selection strategies have been proposed, there is still much work need to do. Inspired by the black stork foraging process, this paper designs a new cognitive selection strategy, in which the whole swarm is divided into adult and infant particle, and each kind particle has its special choice. Simulation results show this new strategy is superior to other two previous modifications.
Keywords
cognition; learning (artificial intelligence); particle swarm optimisation; black stork foraging process; cognitive learning factor; cognitive parameter setting; cognitive selection strategy; particle swarm optimization; selection strategies; Acceleration; Animals; Automation; Competitive intelligence; Computational intelligence; Hybrid intelligent systems; Laboratories; Particle swarm optimization; Process design; Stochastic processes; black stork foraging process; cognitive learning factor; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location
Shenyang
Print_ISBN
978-0-7695-3745-0
Type
conf
DOI
10.1109/HIS.2009.80
Filename
5254321
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