Prediction of health-related leave days among workers in the energy sector by means of genetic algorithms

dc.contributor.author	González Fuentes, Aroa
dc.contributor.author	Busto Serrano, Nélida
dc.contributor.author	Sánchez Lasheras, Fernando
dc.contributor.author	Fidalgo Valverde, Gregorio
dc.contributor.author	Suárez Sánchez, Ana
dc.date.accessioned	2020-09-24T07:44:01Z
dc.date.available	2020-09-24T07:44:01Z
dc.date.issued	2020
dc.identifier.citation	Energies, 13(10), p. 2475- (2020); doi:10.3390/en13102475
dc.identifier.issn	1996-1073
dc.identifier.uri	http://hdl.handle.net/10651/56602
dc.format.extent	p. 2475-
dc.language.iso	eng
dc.relation.ispartof	Energies
dc.rights	© 2020 los autores
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-s2.0-85085000730&doi=10.3390%2fen13102475&partnerID=40&md5=bc903646f189ce462ecdb1cbb985277d
dc.title	Prediction of health-related leave days among workers in the energy sector by means of genetic algorithms
dc.type	journal article
dc.identifier.doi	10.3390/en13102475
dc.relation.publisherversion	http://dx.doi.org/10.3390/en13102475
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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