The invention discloses an urban road network traffic speed prediction method and related equipment, and belongs to the technical field of urban road network traffic speed prediction.An urban road network traffic speed prediction model is established based on an STGAT-LSTM deep learning combination model, spatial correlation of static factors can be extracted based on a graph attention network, and the prediction accuracy of the urban road network traffic speed is improved. And the time correlation of dynamic factors is captured by using a long-short-term memory network, so that accurate prediction of the traffic speed of the urban road network is realized. The urban road network traffic speed prediction method provided by the invention enriches a road network traffic speed prediction method system, and effectively solves the problems that the existing research does not comprehensively consider influence factors in urban road network traffic speed prediction and the model is not widely applicable.

    本发明公开了一种城市路网交通速度预测方法及相关设备,属于城市路网交通速度预测技术领域,城市路网交通速度预测模型基于STGAT‑LSTM深度学习组合模型建立,不仅可以基于图注意力网络提取静态因素的空间相关性,还使用长短期记忆网络捕捉动态因素的时间相关性,从而实现了对城市路网交通速度的精准预测。本发明所提出的城市路网交通速度预测方法丰富了路网交通速度预测方法体系,有效解决了现有研究对城市路网交通速度预测考虑影响因素不全面、模型适用不广泛的问题。


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    Title :

    Urban road network traffic speed prediction method and related equipment


    Additional title:

    一种城市路网交通速度预测方法及相关设备


    Contributors:
    CHEN JUN (author) / CHAI BIN (author) / WANG YUDONG (author)

    Publication date :

    2025-03-14


    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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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