The invention discloses a few-sample traffic flow prediction method and system based on a diffusion model, and a terminal, and the method comprises the steps: obtaining the traffic flow data of a city, and enabling the city to comprise a source city and a target city; constructing a space-time prediction model, and training the space-time prediction model according to the traffic flow data to obtain a high-dimensional vector; acquiring spatial-temporal characteristic data of a city, and processing the spatial-temporal characteristic data to obtain a spatial-temporal characteristic embedded vector; constructing a diffusion model, and training the diffusion model according to the high-dimensional vector and the spatio-temporal feature embedded vector to obtain a trained diffusion model; and based on the trained diffusion model, performing traffic flow prediction on the target city according to the traffic flow data to obtain a traffic flow prediction result. According to the method, the diffusion generation model is introduced before target domain prediction to generate the adaptive model parameters more conforming to the target domain characteristics, so that the future traffic flow is predicted in combination with the traffic flow characteristics of the target domain, and the traffic flow prediction accuracy is improved.

    本申请公开了基于扩散模型的少样本交通流预测方法、系统及终端,所述方法包括:获取城市的交通流数据,其中,城市包括源城市和目标城市;构建时空预测模型,并根据交通流数据对时空预测模型进行训练,得到高维向量;获取城市的时空特征数据,对时空特征数据进行处理,得到时空特征嵌入向量;构建扩散模型,根据高维向量和时空特征嵌入向量对扩散模型进行训练,得到训练好的扩散模型;基于训练好的扩散模型,根据交通流数据对目标城市进行交通流预测,得到交通流预测结果。本申请通过在目标域预测之前引入了扩散生成模型,以生成更符合目标域特征的自适应模型参数,从而结合目标域的交通流特征预测未来交通流,提高了交通流预测准确性。


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    Title :

    Diffusion model-based few-sample traffic flow prediction method, system and terminal


    Additional title:

    基于扩散模型的少样本交通流预测方法、系统及终端


    Contributors:
    CAO YUEHAO (author) / LI YOU (author) / WANG LULU (author) / YUE XIMING (author) / LI MINMIN (author) / YAO MENGMENG (author) / GUO RENZHONG (author)

    Publication date :

    2025-05-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

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



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