The invention discloses a traffic distribution prediction method based on feature extraction and deep learning, and the method comprises the steps: inputting the features of a departure traffic cell and an arrival traffic cell into a trained deep learning prediction model, and obtaining predicted traffic distribution, namely, the traffic volume between the departure traffic cell and the arrival traffic cell. According to the invention, the traffic distribution among the traffic zones can be predicted with high precision, a basis is provided for traffic planning and traffic control, and the method has high popularization and application values.

    本发明公开了一种基于特征提取与深度学习的交通分布预测方法,将出发交通小区和到达交通小区的特征输入训练好的深度学习预测模型中,得到预测的交通分布,即出发交通小区与到达交通小区之间的交通量。本发明能够高精度地预测各交通小区之间的交通分布,为交通规划与交通管控提供依据,具有较高的推广应用价值。


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    Titel :

    Traffic distribution prediction method based on feature extraction and deep learning


    Weitere Titelangaben:

    一种基于特征提取与深度学习的交通分布预测方法


    Beteiligte:
    WANG WEI (Autor:in) / YU WEIJIE (Autor:in) / QIN SHAOYANG (Autor:in) / HUA XUEDONG (Autor:in) / ZHAO DE (Autor:in) / CHEN SIYUAN (Autor:in)

    Erscheinungsdatum :

    03.12.2021


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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