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Article: Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network

TitlePredicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network
Authors
Ke, JQin, XYang, HZheng, ZZhu, ZYe, J
Issue Date2021
Citation
Transportation Research Part C: Emerging Technologies, 2021, v. 122, p. 102858 How to Cite?
DOI: http://dx.doi.org/10.1016/j.trc.2020.102858
Persistent Identifierhttp://hdl.handle.net/10722/320998
ISI Accession Number ID
WOS:000606754900005

 

DC FieldValueLanguage
dc.contributor.authorKe, J-
dc.contributor.authorQin, X-
dc.contributor.authorYang, H-
dc.contributor.authorZheng, Z-
dc.contributor.authorZhu, Z-
dc.contributor.authorYe, J-
dc.date.accessioned2022-11-01T04:45:05Z-
dc.date.available2022-11-01T04:45:05Z-
dc.date.issued2021-
dc.identifier.citationTransportation Research Part C: Emerging Technologies, 2021, v. 122, p. 102858-
dc.identifier.urihttp://hdl.handle.net/10722/320998-
dc.languageeng-
dc.relation.ispartofTransportation Research Part C: Emerging Technologies-
dc.titlePredicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network-
dc.typeArticle-
dc.identifier.emailKe, J: kejintao@hku.hk-
dc.identifier.authorityKe, J=rp02901-
dc.identifier.doi10.1016/j.trc.2020.102858-
dc.identifier.hkuros340787-
dc.identifier.volume122-
dc.identifier.spage102858-
dc.identifier.epage102858-
dc.identifier.isiWOS:000606754900005-

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