Optimizing predictor variables in artificial neural networks when forecasting raw material prices for energy production

dc.contributor.author	Matyjaszek, Marta Janyna
dc.contributor.author	Fidalgo Valverde, Gregorio
dc.contributor.author	Krzemien, A.
dc.contributor.author	Wodarski, K.
dc.contributor.author	Riesgo Fernández, Pedro
dc.date.accessioned	2020-09-24T07:44:07Z
dc.date.available	2020-09-24T07:44:07Z
dc.date.issued	2020
dc.identifier.citation	Energies, 13(8), p. 2017- (2020); doi:10.3390/en13082017
dc.identifier.issn	1996-1073
dc.identifier.uri	http://hdl.handle.net/10651/56646
dc.format.extent	p. 2017-
dc.language.iso	eng
dc.relation.ispartof	Energies
dc.rights	© 2020 Matyjaszek et al.
dc.rights	CC Reconocimiento 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084059107&doi=10.3390%2fen13082017&partnerID=40&md5=a0d2ac051e3a4ad4e79b70e39ff58418
dc.title	Optimizing predictor variables in artificial neural networks when forecasting raw material prices for energy production
dc.type	journal article
dc.identifier.doi	10.3390/en13082017
dc.relation.publisherversion	http://dx.doi.org/10.3390/en13082017
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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