A newly established crossing traffic flow prediction method based on a generating type deep belief network belongs to the technical field of short-period traffic flow prediction. The newly established crossing traffic flow prediction method settles the problems of small amount of data and low prediction precision in traffic flow prediction for a newly established crossing. The newly established crossing traffic flow prediction method comprises the steps of establishing a generating type deep belief network regression model with a 144 input structure and a 144 output structure based on a deep learning theory and a restricted Boltzmann machine; performing pre-training on the deep belief network regression model through mature crossing data of a city to which the newly established crossing is affiliated, and obtaining a deep belief network regression pre-training model; performing fine adjustment on the deep belief network regression pre-training model by means of prestored actual traffic flow data of the newly established crossing, and obtaining a final deep belief network regression model; and acquiring the current actual traffic flow data of the newly established crossing, and performing online prediction on the traffic flow by means of the final deep belief network regression model. The newly established crossing traffic flow prediction method is used for predicting the traffic flow of the newly established crossing.


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    Title :

    Newly established crossing traffic flow prediction method based on generating type deep belief network


    Contributors:
    LIU HUI (author) / WAN JIE (author) / LIU XIN (author) / REN GUORUI (author) / HUANG JIANHUA (author) / LIU ZHI (author) / LI MEILAN (author) / YU SHENG (author)

    Publication date :

    2015-11-25


    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



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