Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques

dc.contributor.author	García Nieto, Paulino José
dc.contributor.author	García Gonzalo, María Esperanza
dc.contributor.author	Sánchez Lasheras, Fernando
dc.contributor.author	Paredes Sánchez, José Pablo
dc.contributor.author	Riesgo Fernández, Pedro
dc.date.accessioned	2019-08-21T07:34:09Z
dc.date.available	2019-08-21T07:34:09Z
dc.date.issued	2019
dc.identifier.citation	Journal of Computational and Applied Mathematics, 357, p. 284-301 (2019); doi:10.1016/j.cam.2019.03.009
dc.identifier.issn	0377-0427
dc.identifier.uri	http://hdl.handle.net/10651/52251
dc.format.extent	p. 284-301
dc.language.iso	eng
dc.relation.ispartof	Journal of Computational and Applied Mathematics, 357
dc.rights	© 2019 Elsevier
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062998133&doi=10.1016%2fj.cam.2019.03.009&partnerID=40&md5=2c34ccd729594c74251ad634e888f0f6
dc.title	Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques
dc.type	journal article
dc.identifier.doi	10.1016/j.cam.2019.03.009
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.cam.2019.03.009

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