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dcterms:bibliographicCitation <http://dblp.uni-trier.de/rec/bibtex/conf/smartgridcomm/TheileTKCPTN18>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Alessandro_Crosara>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Anna-Linnea_Towle>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Graham_Turk>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Kaustubh_Karnataki>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Kaveh_Paridari>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Lars_Nordstr%E2%88%9A%E2%88%82m>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Philipp_Theile>
foaf:homepage <http://dx.doi.org/doi.org%2F10.1109%2FSmartGridComm.2018.8587591>
foaf:homepage <https://doi.org/10.1109/SmartGridComm.2018.8587591>
dc:identifier DBLP conf/smartgridcomm/TheileTKCPTN18 (xsd:string)
dc:identifier DOI doi.org%2F10.1109%2FSmartGridComm.2018.8587591 (xsd:string)
dcterms:issued 2018 (xsd:gYear)
rdfs:label Day-ahead electricity consumption prediction of a population of households: analyzing different machine learning techniques based on real data from RTE in France. (xsd:string)
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Alessandro_Crosara>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Anna-Linnea_Towle>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Graham_Turk>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Kaustubh_Karnataki>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Kaveh_Paridari>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Lars_Nordstr%E2%88%9A%E2%88%82m>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Philipp_Theile>
swrc:pages 1-6 (xsd:string)
dcterms:partOf <https://dblp.l3s.de/d2r/resource/publications/conf/smartgridcomm/2018>
owl:sameAs <http://bibsonomy.org/uri/bibtexkey/conf/smartgridcomm/TheileTKCPTN18/dblp>
owl:sameAs <http://dblp.rkbexplorer.com/id/conf/smartgridcomm/TheileTKCPTN18>
rdfs:seeAlso <http://dblp.uni-trier.de/db/conf/smartgridcomm/smartgridcomm2018.html#TheileTKCPTN18>
rdfs:seeAlso <https://doi.org/10.1109/SmartGridComm.2018.8587591>
swrc:series <https://dblp.l3s.de/d2r/resource/conferences/smartgridcomm>
dc:title Day-ahead electricity consumption prediction of a population of households: analyzing different machine learning techniques based on real data from RTE in France. (xsd:string)
dc:type <http://purl.org/dc/dcmitype/Text>
rdf:type swrc:InProceedings
rdf:type foaf:Document