Abstract Urban railway network traffic prediction is a fundamental capability method as smart transportation technologies. Urban railway traffic prediction is a need that traffic authorities have begun demanding with a rapid increase in the number of passenger flow. Contemporary smart transportation technologies require the traffic prediction capability to be both available and scalable to apply to urban networks. In this paper, spatiotemporal correlations matrix method will be presented to traffic prediction.


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    Titel :

    Urban Railway Network Traffic Prediction with Spatiotemporal Correlations Matrix


    Beteiligte:
    Shao, Weijuan (Autor:in) / Li, Man (Autor:in)


    Ausgabe :

    1st ed. 2016


    Erscheinungsdatum :

    2016-01-01


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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