The invention discloses a traffic flow prediction method based on multi-feature fusion, and the method comprises the steps: carrying out the data cleaning and missing value filling of a traffic data set of a seaport road network, carrying out the data analysis of the daily periodicity, weekly periodicity and holiday periodicity, generating a periodic coding feature, and carrying out the prediction of the traffic flow through combining with weather features and historical flow data. The attention feature fusion method is used for carrying out feature fusion engineering on the features, structured data are input into the recurrent neural network, time sequence prediction training is carried out, the model can carry out synchronous prediction on the complete road network traffic flow, and the prediction accuracy is improved while the calculation requirement is reduced.

    本发明公开了一种基于多特征融合的交通流预测方法:首先对海口市路网交通数据集进行数据清洗和缺失值填充,然后对其日周期性、周周期性和节假日周期性进行数据分析,生成周期性编码特征,然后结合天气特征和历史流量数据,使用注意力特征融合方法对以上特征进行特征融合工程,将结构化数据输入至循环神经网络,进行时间序列预测训练,该模型可以对完整的路网交通流进行同步预测,在降低计算需求的同时提高了预测准确性。


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    Title :

    Traffic flow prediction method based on multi-feature fusion


    Additional title:

    一种基于多特征融合的交通流预测方法


    Contributors:
    LIU CONG'AI (author) / QIN YUHUA (author) / ZHANG XIAOJING (author)

    Publication date :

    2024-03-19


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    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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