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Nearest Neighbor Interaction PSO Based on Small-World Model

  • Conference paper
Intelligent Data Engineering and Automated Learning - IDEAL 2009 (IDEAL 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5788))

  • 1950 Accesses

Abstract

Particle swarm optimization with passive congregation (PSOPC) is a novel variant of particle swarm optimization (PSO) by simulating the animal congregation phenomenon. Although it is superior to the standard version in some cases, however, due to the randomly selected neighbor particle, the performance of PSOPC is not always stable. Therefore, in this paper, a new variant – nearest neighbor interaction particle swarm optimization based on small world model (NNISW) is designed to solve this problem. In NNISW, the additional congregation item is associated with the best particle, nor the random ones, and the small world topology structure is introduced also to simulate the true swarm behavior. After compared with other seven famous benchmarks in high-dimensional cases, the performance of this new variant is superior to other three variants of PSO.

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Authors and Affiliations

  1. Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, Shanxi, P.R. China, 030024

    Zhihua Cui, Yongfang Chu & Xingjuan Cai

Authors
  1. Zhihua Cui
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  2. Yongfang Chu
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  3. Xingjuan Cai
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Editor information

Editors and Affiliations

  1. Escuela Politécnica Superior, Universidad de Burgos, Calle Francisco de Vitoria, S/N, Edifico C, 09006, Burgos, Spain

    Emilio Corchado

  2. School of Electrical and Electronic Engineering, University of Manchester, Sackville Street Building, Sackville Street, M60 1QD, Manchester, UK

    Hujun Yin

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© 2009 Springer-Verlag Berlin Heidelberg

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Cui, Z., Chu, Y., Cai, X. (2009). Nearest Neighbor Interaction PSO Based on Small-World Model. In: Corchado, E., Yin, H. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2009. IDEAL 2009. Lecture Notes in Computer Science, vol 5788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04394-9_77

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  • DOI: https://doi.org/10.1007/978-3-642-04394-9_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04393-2

  • Online ISBN: 978-3-642-04394-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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