Link travel time prediction is a focus of intelligent transportation system (ITS) research. Through comparing the performances of the existing prediction algorithm, this article tries to integrate rough set and BP neural network to establish a new one for link travel time prediction. By comparing the predicted values of travel time to the real travel time, the predicted model is verified to be effective.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Link Travel Time Prediction Based on the Integration of Rough Set and BP Neural Network


    Beteiligte:
    Yao, Chen (Autor:in) / Henk, J. Van Zuylen (Autor:in) / Luo, Xia (Autor:in) / Liu, Haixu (Autor:in)

    Kongress:

    Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    2009-07-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Link Travel Time Prediction Based on the Integration of Rough Set and BP Neural Network

    Yao, C. / Van Zuylen Henk, J. / Luo, X. et al. | British Library Conference Proceedings | 2009


    Link-level Travel Time Prediction Using Artificial Neural Network Models

    Mane, Ajinkya S. / Pulugurtha, Srinivas S. | IEEE | 2018


    Travel time prediction with LSTM neural network

    Yanjie Duan, / Yisheng Lv, / Fei-Yue Wang, | IEEE | 2016


    A Rough Set Model for Travel Time Prediction

    Liu, Hao / Zhang, Xiaoliang / Zhang, Ke | ASCE | 2010


    Link Travel Time Estimation Based on Vehicle Infrastructure Integration Probe Data

    Zou, Z. / Li, M. / Bu, F. et al. | British Library Conference Proceedings | 2010