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Description
  • This chapter presents a new concept of parallel Bivariate Marginal Distribution Algorithm (BMDA) using the stepping stone communication model with the unidirectional ring topology. The traditional migration of individuals is compared with a newly proposed technique of probability model migration. The idea of the new adaptive BMDA (aBMDA) algorithms is to modify the classic learning of the probability model (applied in the sequential BMDA). In the proposed strategy, the adap-tive learning of the resident probability model is used. The evaluation of pair dependency, using Pearson's chi-square statistics is influenced by the relevant immigrant pair dependency according to the quality of resident and immigrant subpopulation. Experimental results show that the proposed aBMDA significantly outperforms the traditional concept of migration of individuals.
  • This chapter presents a new concept of parallel Bivariate Marginal Distribution Algorithm (BMDA) using the stepping stone communication model with the unidirectional ring topology. The traditional migration of individuals is compared with a newly proposed technique of probability model migration. The idea of the new adaptive BMDA (aBMDA) algorithms is to modify the classic learning of the probability model (applied in the sequential BMDA). In the proposed strategy, the adap-tive learning of the resident probability model is used. The evaluation of pair dependency, using Pearson's chi-square statistics is influenced by the relevant immigrant pair dependency according to the quality of resident and immigrant subpopulation. Experimental results show that the proposed aBMDA significantly outperforms the traditional concept of migration of individuals. (en)
Title
  • Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration
  • Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration (en)
skos:prefLabel
  • Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration
  • Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration (en)
skos:notation
  • RIV/00216305:26230/08:PU76810!RIV10-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/07/0850), Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 385871
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/08:PU76810
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • BMDA, Model migration, parallel architectures (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F4DBBFE7A622]
http://linked.open...i/riv/mistoVydani
  • Berlin / Heidelberg
http://linked.open...vEdiceCisloSvazku
  • LNSC, Studies in Computational Intelligence Vol. 1
http://linked.open...i/riv/nazevZdroje
  • Linkage in Evolutionary Computation
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...v/pocetStranKnihy
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Jaroš, Jiří
  • Schwarz, Josef
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-540-85067-0
http://localhost/t...ganizacniJednotka
  • 26230
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