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Chaos Driven PSO with Attractive Search Space Border Points

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241912" target="_blank" >RIV/61989100:27240/18:10241912 - isvavai.cz</a>

  • Alternative codes found

    RIV/70883521:28140/18:63520480

  • Result on the web

    <a href="https://ieeexplore.ieee.org/abstract/document/8477960" target="_blank" >https://ieeexplore.ieee.org/abstract/document/8477960</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Chaos Driven PSO with Attractive Search Space Border Points

  • Original language description

    In this paper, a chaotic pseudorandom generator is used to enhance the performance of Particle Swarm Optimization with attractive search space borders. The original modification was proposed to prolong the exploration phase and improve the ability of the swarm to avoid local minima. The particles are randomly attracted towards the border points of the search space in each dimension. The well-known and frequently used CEC&apos; 13 Benchmark function set is used to test the performance of the proposed method and compare it to canonical PSO.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

  • ISBN

    978-1-5090-6017-7

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    6

  • Pages from-to

    1147-1152

  • Publisher name

    IEEE

  • Place of publication

    Vienna

  • Event location

    Rio de Janeiro

  • Event date

    Jul 8, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000451175500147