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Advanced Parallel Copula Based EDA

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU122834" target="_blank" >RIV/00216305:26230/16:PU122834 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fit.vut.cz/research/publication/11225/" target="_blank" >https://www.fit.vut.cz/research/publication/11225/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/SSCI.2016.7850202" target="_blank" >10.1109/SSCI.2016.7850202</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Advanced Parallel Copula Based EDA

  • Original language description

    Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that are based on building and sampling a probability model. Copula theory provides methods that simplify the estimation of the probability model. To improve the efficiency of current copula based EDAs (CEDAs) new modifications of parallel CEDA were proposed. We investigated eight variants of island-based algorithms utilizing the capability of promising copula families, inter-island migration and additional adaptation of marginal parameters using CT-AVS technique. The proposed algorithms were tested on two sets of well-known standard optimization benchmarks in the continuous domain. The results of the experiments validate the efficiency of our algorithms.

  • 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

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2016 IEEE Symposium Series on Computational Intelligence

  • ISBN

    978-1-5090-4239-5

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1-8

  • Publisher name

    Institute of Electrical and Electronics Engineers

  • Place of publication

    Athens

  • Event location

    Athens

  • Event date

    Dec 6, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000400488302108