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Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction.

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Bibliographic Details
Title: Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction.
Authors: Xu, Yuanbo1, Cai, Xiao1, Wang, En1, Liu, Wenbin1, Yang, Yongjian1, Yang, Funing1
Source: Information Sciences; Apr2023, Vol. 621, p580-595, 16p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 161726839
AccessLevel: 2
PubType: Periodical
PubTypeId: serialPeriodical
PreciseRelevancyScore: 0
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=161726839
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ins.2022.11.086
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 580
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      – TitleFull: Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction.
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            NameFull: Xu, Yuanbo
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            NameFull: Cai, Xiao
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            NameFull: Wang, En
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            NameFull: Liu, Wenbin
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            NameFull: Yang, Yongjian
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            NameFull: Yang, Funing
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          Dates:
            – D: 01
              M: 04
              Text: Apr2023
              Type: published
              Y: 2023
          Identifiers:
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              Value: 00200255
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            – Type: volume
              Value: 621
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            – TitleFull: Information Sciences
              Type: main
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