Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU112086" target="_blank" >RIV/00216305:26230/14:PU112086 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/FOCI.2014.7007815" target="_blank" >http://dx.doi.org/10.1109/FOCI.2014.7007815</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/FOCI.2014.7007815" target="_blank" >10.1109/FOCI.2014.7007815</a>
Alternative languages
Result language
angličtina
Original language name
Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration
Original language description
The paper presents a new concept of an island-based model of Estimation of Distribution Algorithms (EDAs) with a bidirectional topology in the field of numerical optimization in continuous domain. The traditional migration of individuals is replaced by the probability model migration. Instead of a classical joint probability distribution model, the multivariate Gaussian copula is used which must be specified by correlation coefficients and parameters of a univariate marginal distributions. The idea of the proposed Gaussian Copula EDA algorithm with model migration (GC-mEDA) is to modify the parameters of a resident model respective to each island by the immigrant model of the neighbour island. The performance of the proposed algorithm is tested over a group of five well-known benchmarks.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Proceedings
ISBN
978-1-4799-4492-7
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
114-119
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Piscataway
Event location
Orlando
Event date
Dec 9, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000380480600016