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题名: A novel particle swarm optimizer using optimal foraging theory
作者: Niu B(牛奔) ; Zhu YL(朱云龙) ; Hu KY(胡琨元) ; Li SF(李素粉) ; He XX(何小贤)
作者部门: 先进制造技术实验室
会议名称: International Conference on Intelligent Computing (ICIC)
会议日期: August 16-19, 2006
会议地点: Kunming, China
会议主办者: IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China
会议录: COMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS
会议录出版者: SPRINGER-VERLAG
会议录出版地: BERLIN
出版日期: 2006
页码: 61-71
收录类别: SCI ; CPCI(ISTP) ; EI
ISSN号: 0302-9743
ISBN号: 3-540-37277-6
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.
语种: 英语
产权排序: 1
WOS记录号: WOS:000240085400007
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8158
Appears in Collections:工业信息学研究室_先进制造技术研究室_会议论文

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Recommended Citation:
牛奔; 朱云龙; 胡琨元; 李素粉; 何小贤.A novel particle swarm optimizer using optimal foraging theory.见:SPRINGER-VERLAG.COMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS,BERLIN,2006,61-71
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