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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F14%3A00077069%21RIV15-MSM-14330___
rdf:type
n13:Vysledek skos:Concept
dcterms:description
The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy. The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy.
dcterms:title
Emission prediction of a thermal power plant Emission prediction of a thermal power plant
skos:prefLabel
Emission prediction of a thermal power plant Emission prediction of a thermal power plant
skos:notation
RIV/00216224:14330/14:00077069!RIV15-MSM-14330___
n3:aktivita
n16:S
n3:aktivity
S
n3:dodaniDat
n9:2015
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n20:D
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
14418
n3:idVysledku
RIV/00216224:14330/14:00077069
n3:jazykVysledku
n19:eng
n3:klicovaSlova
meta-learning; model prediction; boiler; NOx
n3:klicoveSlovo
n4:NOx n4:model%20prediction n4:boiler n4:meta-learning
n3:kontrolniKodProRIV
[F385646E3321]
n3:mistoKonaniAkce
Jasná pod Chopkom, Nízké Tatry, Slovakia
n3:mistoVydani
Praha
n3:nazevZdroje
Znalosti 2014
n3:obor
n14:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
3
n3:rokUplatneniVysledku
n9:2014
n3:tvurceVysledku
Popelínský, Lubomír Křehlík, Karel Jurčo, Juraj
n3:typAkce
n12:EUR
n3:zahajeniAkce
2014-01-01+01:00
s:numberOfPages
6
n11:hasPublisher
Vysoká škola ekonomická v Praze
n18:isbn
9788024520544
n15:organizacniJednotka
14330