Traffic flow is a complex, changeful, nonlinear, unstructured, space time-varying and random system. With the foundation and operating of the Intelligent Traffic System, it is imperative to search for a traffic state estimation model, which is suitable for mixed-traffic in China. On the basic of analysis of the multidimensional state characteristics of mixed-traffic, using the Rough Set Theory, the four-dimensional state estimation model is founded. By data discretization and attribute reduction, the two-dimensional decision table is gained, and the rules of multidimensional state estimation in urban traffic system are presented. A case is given and it indicates that this method can eliminate the redundancy information of the system effectively and improve the precision of rule mining.


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    Titel :

    Multidimensional State Estimation Rules in Urban Traffic System Based on Rough Set Theory


    Beteiligte:
    Weng, Xiao-xiong (Autor:in) / Weng, Dan (Autor:in) / Ye, Li-ping (Autor:in)

    Kongress:

    First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    09.07.2007




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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