Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation

Grigorev, A; Mihaita, A-S; Lee, S; Chen, F

Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation

Grigorev, A Mihaita, A-S Lee, S Chen, F

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Transportation Research Part C Emerging Technologies, 2022, 141, pp. 103721
Issue Date:: 2022-08-01

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Field	Value	Language
dc.contributor.author	Grigorev, A
dc.contributor.author	Mihaita, A-S
dc.contributor.author	Lee, S
dc.contributor.author	Chen, F https://orcid.org/0000-0003-4971-8729
dc.date.accessioned	2022-07-25T07:16:07Z
dc.date.available	2022-07-25T07:16:07Z
dc.date.issued	2022-08-01
dc.identifier.citation	Transportation Research Part C Emerging Technologies, 2022, 141, pp. 103721
dc.identifier.issn	0968-090X
dc.identifier.uri	http://hdl.handle.net/10453/159153
dc.language	en
dc.publisher	Elsevier BV
dc.relation	http://purl.org/au-research/grants/arc/LP180100114
dc.relation.ispartof	Transportation Research Part C Emerging Technologies
dc.relation.isbasedon	10.1016/j.trc.2022.103721
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Logistics & Transportation
dc.title	Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation
dc.type	Journal Article
utslib.citation.volume	141
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	15 Commerce, Management, Tourism and Services
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/A/DRsch The Data Science Institute
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2024-08-01T00:00:00+1000Z
dc.date.updated	2022-07-25T07:16:05Z
pubs.publication-status	Accepted
pubs.volume	141

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http://hdl.handle.net/10453/159153