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Link speed prediction for signalized urban traffic network using a hybrid deep learning approach
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering. Smart Transportation Research Institute, Enjoyor Co. Ltd, Hangzhou, 310030, China and Engineering Research Center of Intelligent Transport of Zhejiang Province, Hangzhou 310030, China..
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310013, China ; Enjoyor Co., Ltd, Hangzhou 310030, China..
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2019 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
2019.
National Category
Transport Systems and Logistics Computer Sciences
Research subject
Transport Science, Transport Systems
Identifiers
URN: urn:nbn:se:kth:diva-256047OAI: oai:DiVA.org:kth-256047DiVA, id: diva2:1343496
Conference
22nd IEEE Intelligent Transportation Systems Conference (ITSC 2019), Auckland, New Zealand 27-30 October, 2019
Note

QC 20191003

Available from: 2019-08-16 Created: 2019-08-16 Last updated: 2019-10-03Bibliographically approved

Open Access in DiVA

fulltext(829 kB)1 downloads
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File name FULLTEXT01.pdfFile size 829 kBChecksum SHA-512
3d89d560358761b39254aff4fa5662a5d1dde73f670d08bc00407d7f4bf13f134054d4966ac78ea0c20ddab5bc7a5d2759b269847a8e2b8723976b9bd5facd12
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Ma, Xiaoliang
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf