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.
Multidimensional State Estimation Rules in Urban Traffic System Based on Rough Set Theory
First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China
09.07.2007
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Multidimensional State Estimation Rules in Urban Traffic System Based on Rough Set Theory
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