The invention discloses a short distance driving time prediction method comprising the following steps: S1, using a traffic data acquisition device to collect data, and using a normalization method to carry out pretreatment for the collected data; S2, applying the pretreated data to train a stack autoencoder depth network, thus obtaining an optimal network structure and a corresponding parameter, and generating the optimal stack autoencoder depth network; S3, using the trained optimal stack autoencoder depth network to predict a vehicle short distance driving time. The short distance driving time prediction method can deeply excavate a non-linear relation and other inner characteristics between input variables, is high in prediction precision, and high in robustness.


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    Title :

    Short distance driving time prediction method


    Contributors:
    XIONG GANG (author) / KANG WENWEN (author) / ZHU FENGHUA (author) / WANG FEIYUE (author) / LYU YISHENG (author) / DONG XISONG (author)

    Publication date :

    2015-09-09


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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