IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/976486.html
   My bibliography  Save this article

An Improved Particle Swarm Optimization Algorithm Based on Centroid and Exponential Inertia Weight

Author

Listed:
  • Shouwen Chen
  • Zhuoming Xu
  • Yan Tang
  • Shun Liu

Abstract

Particle swarm optimization algorithm (PSO) is a global stochastic tool, which has ability to search the global optima. However, PSO algorithm is easily trapped into local optima with low accuracy in convergence. In this paper, in order to overcome the shortcoming of PSO algorithm, an improved particle swarm optimization algorithm (IPSO), based on two forms of exponential inertia weight and two types of centroids, is proposed. By means of comparing the optimization ability of IPSO algorithm with BPSO, EPSO, CPSO, and ACL-PSO algorithms, experimental results show that the proposed IPSO algorithm is more efficient; it also outperforms other four baseline PSO algorithms in accuracy.

Suggested Citation

  • Shouwen Chen & Zhuoming Xu & Yan Tang & Shun Liu, 2014. "An Improved Particle Swarm Optimization Algorithm Based on Centroid and Exponential Inertia Weight," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-14, December.
    • Handle: RePEc:hin:jnlmpe:976486
    DOI: 10.1155/2014/976486
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2014/976486.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2014/976486.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/976486?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kaloop, Mosbeh R. & Bardhan, Abidhan & Kardani, Navid & Samui, Pijush & Hu, Jong Wan & Ramzy, Ahmed, 2021. "Novel application of adaptive swarm intelligence techniques coupled with adaptive network-based fuzzy inference system in predicting photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:976486. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.