The invention discloses a short-time traffic-flow combination prediction method. The method comprises the following steps of step 1, presetting an acquisition period and collecting traffic flow time sequence data of a prediction target point according to the acquisition period; if a prediction day of the prediction target point is not a holiday, collecting traffic flow time sequence data of days in at least adjacent previous three weeks, wherein the days are the same weekday with the prediction day; if the prediction day of the prediction target point is a holiday, collecting traffic flow time sequence data of days in at least adjacent previous three years, wherein the days are the same holiday with the prediction day; step 2, using a set experience modal decomposition method to decompose the traffic flow time sequence data into several intrinsic mode components possessing a same characteristic; step 3, using a BP neural network algorithm to carry out prediction on each intrinsic mode component obtained through decomposition by using the set experience modal decomposition method respectively, superposing prediction results of the intrinsic mode components and acquiring a final prediction result. By using the prediction method in the invention, prediction precision of the short-time traffic flow can be effectively increased.


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    Title :

    Short-time traffic-flow combination prediction method


    Contributors:
    YANG CHUNXIA (author) / FU YIQIN (author) / WU WENLU (author) / ZHANG JIN (author) / BAO TIENAN (author) / NI JUN (author)

    Publication date :

    2015-11-11


    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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