Research on traffic flow prediction method based on combination models

Jun Nie; Weiqing Xie; Wen Zhang

doi:10.1117/12.3009216

16 October 2023 Research on traffic flow prediction method based on combination models

Jun Nie, Weiqing Xie, Wen Zhang

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128032L (2023) https://doi.org/10.1117/12.3009216
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

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.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jun Nie, Weiqing Xie, and Wen Zhang "Research on traffic flow prediction method based on combination models", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128032L (16 October 2023); https://doi.org/10.1117/12.3009216

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