Traffic flow prediction is of significant importance in traffic planning. Currently, traffic flow data are primarily collected through loop detectors. However, factors such as road conditions can affect the accuracy of these data. To address this issue, this paper proposes a traffic flow prediction method based on decomposition and machine learning. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method decomposes the sequence into multiple intrinsic mode functions (IMFs). The complexity of each IMF is calculated using the sample entropy (SE), and then the IMFs are reconstructed. Parameters of the variational mode decomposition (VMD) are optimized using the whale optimization algorithm (WOA) for the secondary decomposition, and predictions are made using gated recurrent units (GRU). Finally, the prediction results are reconstructed to obtain the final prediction values. In the case study section, experiments are conducted using datasets from three detectors to explore different decomposition forms and methods.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic flow prediction for highway vehicle detectors through decomposition and machine learning


    Weitere Titelangaben:

    W. LU ET AL.
    TRANSPORTATION LETTERS


    Beteiligte:
    Lu, Wanlian (Autor:in) / Hu, Yao (Autor:in) / Chen, Wangyong (Autor:in) / Qin, Yutao (Autor:in) / Wu, Chuliang (Autor:in) / He, Xinyi (Autor:in)

    Erschienen in:

    Transportation Letters ; 17 , 2 ; 260-280


    Erscheinungsdatum :

    07.02.2025


    Format / Umfang :

    21 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Highway traffic flow prediction method

    LU QIRONG / JING HONGJIE / YU CHENG et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Highway traffic flow prediction method

    HAO ZHIQIANG / GENG DANYANG / WEN HAO et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Deep learning based traffic flow prediction model on highway research

    Jia, Qingyang / Zang, Jingfeng / Liu, Shuanglin | SPIE | 2024