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postgraduate thesis: A self-learning short-term traffic forecasting system through dynamic hybrid approach

TitleA self-learning short-term traffic forecasting system through dynamic hybrid approach
Authors
Advisors
Advisor(s):Yeh, AGO
Issue Date2007
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
DegreeDoctor of Philosophy
SubjectTraffic estimation - Mathematical models.
Dept/ProgramUrban Planning and Environmental Management

 

DC FieldValueLanguage
dc.contributor.advisorYeh, AGO-
dc.contributor.authorZhu, Jiasong.-
dc.contributor.author朱家松.-
dc.date.issued2007-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.source.urihttp://hub.hku.hk/bib/B39634516-
dc.subject.lcshTraffic estimation - Mathematical models.-
dc.titleA self-learning short-term traffic forecasting system through dynamic hybrid approach-
dc.typePG_Thesis-
dc.identifier.hkulb3963451-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesisleveldoctoral-
dc.description.thesisdisciplineUrban Planning and Environmental Management-
dc.description.naturepublished_or_final_version-
dc.description.natureabstract-
dc.identifier.doi10.5353/th_b3963451-
dc.date.hkucongregation2008-

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