About: Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
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rdfs:seeAlso	http://link.springer.com/chapter/10.1007%2F978-3-319-11298-5_2#page-1
Description	The paper demonstrates the importance of feature selection for recurrent neural network applied to problem of one hour ahead forecasting of thermal comfort for office building heated by gas. Although the accuracy of the forecasting is similar for both the feed-forward and the recurrent network, the removal of features leads to accuracy reduction much earlier for the feed-forward network. The recurrent network can perform well even with less than 50% of features. This brings significant benefits in scenarios, where the neural network is used as a blackbox model of thermal comfort, which is called by an optimizer that minimizes the deviance from a target value. The reduction of input dimensionality can lead to reduction of costs related to measurement equipment, data transfer and also computational demands of optimization. The paper demonstrates the importance of feature selection for recurrent neural network applied to problem of one hour ahead forecasting of thermal comfort for office building heated by gas. Although the accuracy of the forecasting is similar for both the feed-forward and the recurrent network, the removal of features leads to accuracy reduction much earlier for the feed-forward network. The recurrent network can perform well even with less than 50% of features. This brings significant benefits in scenarios, where the neural network is used as a blackbox model of thermal comfort, which is called by an optimizer that minimizes the deviance from a target value. The reduction of input dimensionality can lead to reduction of costs related to measurement equipment, data transfer and also computational demands of optimization. (en)
Title	Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort (en)
skos:prefLabel	Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort (en)
skos:notation	RIV/68407700:21230/14:00219453!RIV15-GA0-21230___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GP13-21696P)
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Macaš, Martin
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	20913
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/14:00219453
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Forecasting; Thermal Comfort; Gas; Heating; Neural Networks; Feature Selection (en)
http://linked.open.../riv/klicoveSlovo	Feature Selection Thermal Comfort Heating Forecasting Gas Neural Networks
http://linked.open...ontrolniKodProRIV	[D2B7BA719B94]
http://linked.open...v/mistoKonaniAkce	Bournemouth
http://linked.open...i/riv/mistoVydani	Heidelberg
http://linked.open...i/riv/nazevZdroje	Adaptive and Intelligent Systems - LNAI 8779
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	8 (xsd:int)
http://linked.open...vavai/riv/projekt	Selekce příznaků pro modely vícedimenzionálních časových řad uvažující časový kontext
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Moretti, F. Macaš, Martin Lauro, F. Pizzuti, S. Annuziato, M. Comodi, G. Fonti, A. Giantomassi, A.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000346932400002
http://linked.open.../riv/zahajeniAkce	2014-09-08 (xsd:date)
issn	0302-9743
number of pages	9 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-319-11298-5_2
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-319-11297-8
http://localhost/t...ganizacniJednotka	21230

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