On the basis of current research on traffic flow prediction, the article proposes a traffic flow prediction method based on the fusion of K-Means algorithm and GRU. This method first uses K-means for clustering analysis of traffic flow and establishes a traffic flow pattern database, and then predicts traffic flow through GRU training. After simulation experiments, the MAPE and RMSE values of the traffic flow prediction method based on the fusion of K-Means and GRU are lower than those of traditional GRU, LSTM, KNN, SAES, and SVM, and the fitting effect is good. It is a reference traffic prediction method.


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    Titel :

    Research on traffic flow prediction method based on combination models


    Beteiligte:
    Zaidi, Habib (Herausgeber:in) / Shmaliy, Yuriy S. (Herausgeber:in) / Meng, Hongying (Herausgeber:in) / Kolivand, Hoshang (Herausgeber:in) / Sun, Yougang (Herausgeber:in) / Luo, Jianping (Herausgeber:in) / Alazab, Mamoun (Herausgeber:in) / Nie, Jun (Autor:in) / Xie, Weiqing (Autor:in) / Zhang, Wen (Autor:in)

    Kongress:

    Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023) ; 2023 ; Wuhan, China


    Erschienen in:

    Proc. SPIE ; 12803


    Erscheinungsdatum :

    16.10.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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