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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F05%3A03115266%21RIV06-MSM-21230___
rdf:type
skos:Concept n20:Vysledek
dcterms:description
In the original Multilayered Iterative Algorithm the exhaustive search is used to find and select units with the best transfer function, connected to most relevant inputs. Recently, several modifications using standard genetic algorithms instead of exhaustive search appeared. This paper shows how to improve the efficiency of search by evolving non-correlated units (active neurons). This is attained by employing Deterministic Crowding (DC) method proposed by Mahfoud in 1995. As a by-product of using DC method, we can estimate the importance of input variables for modelled output (feature ranking). In the original Multilayered Iterative Algorithm the exhaustive search is used to find and select units with the best transfer function, connected to most relevant inputs. Recently, several modifications using standard genetic algorithms instead of exhaustive search appeared. This paper shows how to improve the efficiency of search by evolving non-correlated units (active neurons). This is attained by employing Deterministic Crowding (DC) method proposed by Mahfoud in 1995. As a by-product of using DC method, we can estimate the importance of input variables for modelled output (feature ranking). Není k dispozici
dcterms:title
Deterministic Crowding Helps to Evolve Non-correlated Active Neurons Není k dispozici Deterministic Crowding Helps to Evolve Non-correlated Active Neurons
skos:prefLabel
Není k dispozici Deterministic Crowding Helps to Evolve Non-correlated Active Neurons Deterministic Crowding Helps to Evolve Non-correlated Active Neurons
skos:notation
RIV/68407700:21230/05:03115266!RIV06-MSM-21230___
n3:strany
21 ; 28
n3:aktivita
n21:Z
n3:aktivity
Z(MSM6840770012)
n3:dodaniDat
n9:2006
n3:domaciTvurceVysledku
n4:7035586 n4:1266500
n3:druhVysledku
n7:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
517682
n3:idVysledku
RIV/68407700:21230/05:03115266
n3:jazykVysledku
n10:eng
n3:klicovaSlova
Deterministic Crowding, Niching Genetic Algorithm, Inductive Modelling, GMDH, GAME, Feature Ranking
n3:klicoveSlovo
n11:GAME n11:Feature%20Ranking n11:Niching%20Genetic%20Algorithm n11:Inductive%20Modelling n11:GMDH n11:Deterministic%20Crowding
n3:kontrolniKodProRIV
[BA705D72738F]
n3:mistoKonaniAkce
Kyjev
n3:mistoVydani
Kyjev
n3:nazevZdroje
Proceedings of the International Workshop on Inductive Modeling IWIM-2005
n3:obor
n8:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n9:2005
n3:tvurceVysledku
Šnorek, Miroslav Kordík, Pavel
n3:typAkce
n13:WRD
n3:zahajeniAkce
2005-07-11+02:00
n3:zamer
n19:MSM6840770012
s:numberOfPages
8
n14:hasPublisher
Akademie věd Ukrajiny, ústav kybernetiky V.M.Gluškova
n12:isbn
966-02-3734-0
n17:organizacniJednotka
21230