The invention discloses a traffic flow prediction method based on LSTM-Attention, and the method comprises the steps: collecting historical data, carrying out the preprocessing of the historical data, inputting the processed data into an established LSTM-Attention model, carrying out the training of the LSTM-Attention model, and predicting the traffic flow at a next moment through employing the trained LSTM-Attention model. The prediction accuracy of the method is higher than that of machine learning models such as traditional statistics and single LSTM.

    本发明公开了一种基于LSTM‑Attention的交通流量预测方法,该方法采集历史数据,并对历史数据进行预处理,将处理后的数据输入至建立好的LSTM‑Attention模型中,对该LSTM‑Attention模型进行训练,采用训练好的LSTM‑Attention模型预测下一个时刻的交通流量。本发明的预测准确度高于传统的统计学和单一的LSTM等机器学习模型。


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    Title :

    Traffic flow prediction method based on LSTM-Attention


    Additional title:

    一种基于LSTM-Attention的交通流量预测方法


    Contributors:
    QIN XIAOLIN (author) / LIU JIACHEN (author) / SONG LIXIANG (author) / ZHU RUNZE (author)

    Publication date :

    2021-06-08


    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 / 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



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