Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F08%3APU76810" target="_blank" >RIV/00216305:26230/08:PU76810 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration

Popis výsledku v původním jazyce

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 residentprobability 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 thatthe proposed aBMDA significantly outperforms the traditional concept of migration of individuals.

Název v anglickém jazyce

Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration

Popis výsledku anglicky

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 residentprobability 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 thatthe proposed aBMDA significantly outperforms the traditional concept of migration of individuals.

Druh

C - Kapitola v odborné knize

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F07%2F0850" target="_blank" >GA102/07/0850: Návrh a obvodová realizace zařízení pro automatické generování patentovatelných invencí</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2008

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Linkage in Evolutionary Computation

ISBN

978-3-540-85067-0

Počet stran výsledku

21

Strana od-do

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Počet stran knihy

486

Název nakladatele

Springer Verlag

Místo vydání

Berlin / Heidelberg

Kód UT WoS kapitoly

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