Short-term traffic flow forecasting plays a very important role in urban traffic management and control. In this paper, According to the chaotic property of urban traffic flow, we compute the parameters of phrase space reconstruction for traffic flow system. Meanwhile, a local-forecasting method is introduced to predict urban road short-term traffic flow based on the theory of phrase space reconstruction. Self-organizing Map (SOM) network is introduced to seek the near neighbor. Case study using real traffic flow data from UTC-SCOOT system proves the validity of the method. The research in this paper is a significant attempt to forecast traffic flow from the viewpoint of non-linear time series.


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    Titel :

    An applicable short-term traffic flow forecasting method based on chaotic theory


    Beteiligte:
    Jianming Hu, (Autor:in) / Chunguang Zong, (Autor:in) / Jingyan Song, (Autor:in) / Zuo Zhang, (Autor:in) / Jiangtao Ren, (Autor:in)


    Erscheinungsdatum :

    2003-01-01


    Format / Umfang :

    354700 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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