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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    Title :

    Research on traffic flow prediction method based on combination models


    Contributors:

    Conference:

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


    Published in:

    Proc. SPIE ; 12803


    Publication date :

    2023-10-16





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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