The disclosure involves a method comprising clustering a plurality of observation samples related to historical travel demands into one or more clusters; for each cluster, constructing an actual probability distribution of the historical travel demands corresponding to the observation samples in the cluster; for each cluster, inputting observation samples in the cluster into a prediction model for predicting future travel demands to produce a result of prediction; for each cluster, computing a predicted probability distribution of the historical travel demands corresponding to the observation samples in the cluster based on the result of prediction; for each cluster, evaluating a difference between the actual probability distribution and the predicted probability distribution of the cluster; and modifying the prediction model so that a statistical sum of the differences for the one or more clusters is decreased.


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    Titel :

    Uncertainty modeling in traffic demand prediction


    Beteiligte:
    DONG WEI SHAN (Autor:in) / GAO PENG (Autor:in) / SUN WEI (Autor:in) / YAN JUN CHI (Autor:in) / ZHANG SHI LEI (Autor:in) / ZHANG XIN (Autor:in) / ZHU JUN (Autor:in)

    Erscheinungsdatum :

    2020-04-28


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES



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