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Detail publikačního výsledku
HYRŠ, M.; SCHWARZ, J.
Originální název
Advanced Parallel Copula Based EDA
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
Estimation of distribution algorithms (EDAs) arestochastic optimization techniques that are based on building andsampling a probability model. Copula theory provides methodsthat simplify the estimation of the probability model. To improvethe efficiency of current copula based EDAs (CEDAs) new modificationsof parallel CEDA were proposed. We investigated eightvariants of island-based algorithms utilizing the capability ofpromising copula families, inter-island migration and additionaladaptation of marginal parameters using CT-AVS technique.The proposed algorithms were tested on two sets of well-knownstandard optimization benchmarks in the continuous domain.The results of the experiments validate the efficiency of ouralgorithms.
Anglický abstrakt
Klíčová slova
Estimation of distribution algorithm (EDA)Copula theoryParallel island-based algorithmMigration of modelBenchmarks CEC 2013
Klíčová slova v angličtině
Autoři
Rok RIV
2017
Vydáno
15.08.2016
Nakladatel
Institute of Electrical and Electronics Engineers
Místo
Athens
ISBN
978-1-5090-4239-5
Kniha
2016 IEEE Symposium Series on Computational Intelligence
Strany od
1
Strany do
8
Strany počet
URL
https://www.fit.vut.cz/research/publication/11225/
BibTex
@inproceedings{BUT133499, author="Martin {Hyrš} and Josef {Schwarz}", title="Advanced Parallel Copula Based EDA", booktitle="2016 IEEE Symposium Series on Computational Intelligence", year="2016", pages="1--8", publisher="Institute of Electrical and Electronics Engineers", address="Athens", doi="10.1109/SSCI.2016.7850202", isbn="978-1-5090-4239-5", url="https://www.fit.vut.cz/research/publication/11225/" }
Dokumenty
SSCI16_paper_197