The invention provides a deep learning traffic flow prediction method based on meteorological information fusion, and the method comprises the following steps: 1, carrying out the preprocessing of traffic data and weather data; step 2, establishing a time alignment module to solve the time dislocation problem of traffic data and weather data; step 3, carrying out embedded coding on the traffic data and the weather data; step 4, establishing an enhanced space-time convolutional network, extracting space-time features from the traffic data through the enhanced space-time convolutional network, and extracting time sequence features from the meteorological data through the enhanced space-time convolutional network; 5, establishing a comparative learning module, and performing feature fusion and comparative learning on the spatio-temporal features and the time sequence features; and step 6, generating a predicted value of the traffic flow. According to the method, the defects of an existing traffic flow prediction method in the aspects of multi-source data integration, long-time dependence capture, feature fusion and the like are effectively overcome, and a new technical approach is provided for improving the precision of traffic flow prediction and the universality of practical application.

    本发明提供了基于气象信息融合的深度学习交通流量预测方法,包括以下步骤:步骤1,对交通数据和天气数据进行预处理;步骤2,建立时间对齐模块,解决交通数据与天气数据的时间错位问题;步骤3,对交通数据和天气数据进行嵌入编码;步骤4,建立增强时空卷积网络,交通数据通过增强时空卷积网络提取出时空特征,气象数据通过增强时空卷积网络提取出时序特征;步骤5,建立对比学习模块,对时空特征和时序特征进行特征融合与对比学习;步骤6,生成交通流量的预测值。本发明有效地解决了现有交通流量预测方法在多源数据整合、长时间依赖捕捉以及特征融合等方面的不足,为提升交通流量预测的精度和实际应用的广泛性提供了新的技术途径。


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    Title :

    Deep learning traffic flow prediction method based on meteorological information fusion


    Additional title:

    基于气象信息融合的深度学习交通流量预测方法


    Contributors:
    WANG SEN (author) / LIU WENJIE (author) / LI ZHIGANG (author)

    Publication date :

    2024-12-24


    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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