A study on data-driven hybrid heating load prediction methods in low-temperature district heating: An example for nursing homes in Nordic countries

dc.contributor.author	Ding, Yiyu
dc.contributor.author	Timoudas, Thomas Ohlson
dc.contributor.author	Wang, Qian
dc.contributor.author	Chen, Shuqin
dc.contributor.author	Brattebø, Helge
dc.contributor.author	Nord, Natasa
dc.date.accessioned	2023-01-10T14:58:33Z
dc.date.available	2023-01-10T14:58:33Z
dc.date.created	2022-08-27T21:05:34Z
dc.date.issued	2022
dc.identifier.citation	Energy Conversion and Management. 2022, 269 .	en_US
dc.identifier.issn	0196-8904
dc.identifier.uri	https://hdl.handle.net/11250/3042474
dc.language.iso	eng	en_US
dc.publisher	Elsevier	en_US
dc.rights	Navngivelse 4.0 Internasjonal	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/deed.no	*
dc.title	A study on data-driven hybrid heating load prediction methods in low-temperature district heating: An example for nursing homes in Nordic countries	en_US
dc.title.alternative	A study on data-driven hybrid heating load prediction methods in low-temperature district heating: An example for nursing homes in Nordic countries	en_US
dc.type	Journal article	en_US
dc.type	Peer reviewed	en_US
dc.description.version	publishedVersion	en_US
dc.source.pagenumber	14	en_US
dc.source.volume	269	en_US
dc.source.journal	Energy Conversion and Management	en_US
dc.identifier.doi	10.1016/j.enconman.2022.116163
dc.identifier.cristin	2046462
dc.relation.project	Norges forskningsråd: 268248	en_US
cristin.ispublished	true
cristin.fulltext	postprint
cristin.fulltext	original
cristin.qualitycode	1

Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal