The invention discloses a traffic flow prediction method based on a time-space gated attention map neural network, and the method comprises the steps: collecting feature data used for training a neural network from a public data set, and enabling the feature data to comprise time, space and corresponding traffic flow; the method comprises the following steps: firstly, constructing a neural network based on a time-space gating attention map, training the network by using feature data until the network converges, and then carrying out traffic flow prediction according to the trained network, so that the error of traffic flow prediction can be minimum, and the requirements of practical application are met.

    本发明公开了一种基于时空门控注意力图神经网络的交通流量预测方法,先从公开数据集中采集用于训练神经网络的特征数据,特征数据包含时间、空间及对应车流量三个维度;然后构建基于时空门控注意力图神经网络,并利用特征数据训练网络,直至网络收敛,然后根据训练完成的网络进行交通流量预测,这样能够实现对交通流量预测的误差最小,达到实际应用的需要。


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    Title :

    Traffic flow prediction method based on time-space gated attention map neural network


    Additional title:

    基于时空门控注意力图神经网络的交通流量预测方法


    Contributors:
    XU JIE (author) / GENG ZILI (author) / WU RONGSEN (author) / MIAO KE (author) / XIE LINBING (author) / LI ZIXUAN (author) / LI YIYAO (author)

    Publication date :

    2024-04-05


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / 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



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