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	A novel particle swarm optimizer using optimal foraging theory
	Niu, Ben; Zhu, Yunlong; Hu, Kunyuan; Li, Sufen; He, Xiaoxian
刊名	Computational intelligence and bioinformatics, pt 3, proceedings
	2006
卷号	4115页码:61-71
ISSN号	0302-9743
通讯作者	Niu, ben(niuben@sia.cn)
英文摘要	Based on the research of optimal foraging theory (oft), we present a novel particle swarm optimizer (pso) to improve the performance of standard pso (spso). the resulting algorithm is known as psooft that makes use of two mechanisms of oft: a reproduction strategy to enhance the ability to converge rapidly to good solutions and a patch-choice based scheme to keep a right balance of exploration and exploitation. in the simulation studies, several benchmark functions are performed, and the performance of the proposed algorithm is compared to the standard pso (spso). the experimental results show that the psooft prevents premature convergence to a high degree, but still has a more rapid convergence rate than spso.
WOS关键词	ALGORITHM
WOS研究方向	Biochemistry & Molecular Biology ; Computer Science
WOS类目	Biochemical Research Methods ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods
语种	英语
出版者	SPRINGER-VERLAG BERLIN
WOS记录号	WOS:000240085400007
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2379076
专题	中国科学院大学
通讯作者	Niu, Ben
作者单位	1.Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China
推荐引用方式 GB/T 7714	Niu, Ben,Zhu, Yunlong,Hu, Kunyuan,et al. A novel particle swarm optimizer using optimal foraging theory[J]. Computational intelligence and bioinformatics, pt 3, proceedings,2006,4115:61-71.
APA	Niu, Ben,Zhu, Yunlong,Hu, Kunyuan,Li, Sufen,&He, Xiaoxian.(2006).A novel particle swarm optimizer using optimal foraging theory.Computational intelligence and bioinformatics, pt 3, proceedings,4115,61-71.
MLA	Niu, Ben,et al."A novel particle swarm optimizer using optimal foraging theory".Computational intelligence and bioinformatics, pt 3, proceedings 4115(2006):61-71.

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