Deep spatial-temporal sequence modeling for multi-step passenger demand prediction

Bai, L Yao, L Wang, X

Li, C Zhang, X

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Field	Value	Language
dc.contributor.author	Bai, L
dc.contributor.author	Yao, L
dc.contributor.author	Wang, X https://orcid.org/0000-0001-9582-3445
dc.contributor.author	Li, C
dc.contributor.author	Zhang, X
dc.date.accessioned	2021-03-19T04:52:31Z
dc.date.available	2021-03-19T04:52:31Z
dc.date.issued	2021-03
dc.identifier.citation	Future Generation Computer Systems, 2021
dc.identifier.issn	0167-739X
dc.identifier.uri	http://hdl.handle.net/10453/147381
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Future Generation Computer Systems
dc.relation.isbasedon	10.1016/j.future.2021.03.003
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems
dc.subject.classification	Distributed Computing
dc.title	Deep spatial-temporal sequence modeling for multi-step passenger demand prediction
dc.type	Journal Article
utslib.for	0803 Computer Software
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2022-03-29T00:00:00+1000Z
dc.date.updated	2021-03-19T04:52:29Z
pubs.publication-status	Published

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