File Download
 
 
Supplementary

Postgraduate Thesis: A self-learning short-term traffic forecasting system through dynamic hybrid approach
  • Basic View
  • Metadata View
  • XML View
TitleA self-learning short-term traffic forecasting system through dynamic hybrid approach
 
AuthorsZhu, Jiasong.
朱家松.
 
Issue Date2007
 
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
 
AdvisorsYeh, AGO
 
DegreeDoctor of Philosophy
 
SubjectTraffic estimation - Mathematical models.
 
Dept/ProgramUrban Planning and Environmental Management
 
DOIhttp://dx.doi.org/10.5353/th_b3963451
 
DC FieldValue
dc.contributor.advisorYeh, AGO
 
dc.contributor.authorZhu, Jiasong.
 
dc.contributor.author朱家松.
 
dc.date.hkucongregation2008
 
dc.date.issued2007
 
dc.description.naturepublished_or_final_version
 
dc.description.natureabstract
 
dc.description.thesisdisciplineUrban Planning and Environmental Management
 
dc.description.thesisleveldoctoral
 
dc.description.thesisnameDoctor of Philosophy
 
dc.identifier.doihttp://dx.doi.org/10.5353/th_b3963451
 
dc.identifier.hkulb3963451
 
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
 
<?xml encoding="utf-8" version="1.0"?>
<item><contributor.advisor>Yeh, AGO</contributor.advisor>
<contributor.author>Zhu, Jiasong.</contributor.author>
<contributor.author>&#26417;&#23478;&#26494;.</contributor.author>
<date.issued>2007</date.issued>
<language>eng</language>
<publisher>The University of Hong Kong (Pokfulam, Hong Kong)</publisher>
<relation.ispartof>HKU Theses Online (HKUTO)</relation.ispartof>
<rights>The author retains all proprietary rights, (such as patent rights) and the right to use in future works.</rights>
<rights>Creative Commons: Attribution 3.0 Hong Kong License</rights>
<source.uri>http://hub.hku.hk/bib/B39634516</source.uri>
<subject.lcsh>Traffic estimation - Mathematical models.</subject.lcsh>
<title>A self-learning short-term traffic forecasting system through dynamic hybrid approach</title>
<type>PG_Thesis</type>
<identifier.hkul>b3963451</identifier.hkul>
<description.thesisname>Doctor of Philosophy</description.thesisname>
<description.thesislevel>doctoral</description.thesislevel>
<description.thesisdiscipline>Urban Planning and Environmental Management</description.thesisdiscipline>
<description.nature>published_or_final_version</description.nature>
<description.nature>abstract</description.nature>
<identifier.doi>10.5353/th_b3963451</identifier.doi>
<date.hkucongregation>2008</date.hkucongregation>
<bitstream.url>http://hub.hku.hk/bitstream/10722/54469/5/Abstract.pdf</bitstream.url>
<bitstream.url>http://hub.hku.hk/bitstream/10722/54469/6/FullText.pdf</bitstream.url>
</item>