The invention discloses a traffic flow prediction method based on a deep learning nerve network structure. Various kinds of traffic flow data are collected, a depth automatic encoder model is utilized for training the collected various kinds of traffic flow data, the depth automatic encoder model is adjusted in the training process, and finally, the adjusted depth automatic encoder model is used for predicting a short-period traffic flow. By adopting the method, deeper excavation analysis is carried out on traffic flow data, so that the short-period prediction of the traffic flow is more accurate, and the performance is better.


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    Titel :

    Traffic flow prediction method based on deep learning nerve network structure


    Beteiligte:
    HUANG BUTIAN (Autor:in) / FANG JIULIN (Autor:in)

    Erscheinungsdatum :

    16.12.2015


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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