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Detail publikačního výsledku
HYRŠ, M.; SCHWARZ, J.
Originální název
Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that are based on buildingand sampling a probability model. Copula theory provides methods that simplify the estimation of a probabilitymodel. An island-based version of copula-based EDA with probabilistic model migration (mCEDA) wastested on a set of well-known standard optimization benchmarks in the continuous domain. We investigatedtwo families of copulas - Archimedean and elliptical. Experimental results confirm that this concept of modelmigration (mCEDA) yields better convergence as compared with the sequential version (sCEDA) and otherrecently published copula-based EDAs.
Anglický abstrakt
Klíčová slova
Estimation of Distribution Algorithms, Copula Theory, Parallel EDA, Island-based Model, MultivariateCopula Sampling, Migration of Probabilistic Models.
Klíčová slova v angličtině
Autoři
Rok RIV
2016
Vydáno
12.11.2015
Nakladatel
SciTePress - Science and Technology Publications
Místo
Lisbon
ISBN
978-989-758-157-1
Kniha
Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)
Strany od
212
Strany do
219
Strany počet
8
URL
https://www.fit.vut.cz/research/publication/11013/
BibTex
@inproceedings{BUT119927, author="Martin {Hyrš} and Josef {Schwarz}", title="Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration", booktitle="Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)", year="2015", pages="212--219", publisher="SciTePress - Science and Technology Publications", address="Lisbon", isbn="978-989-758-157-1", url="https://www.fit.vut.cz/research/publication/11013/" }
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