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Accurate traffic flow forecasting is crucial to the development of intelligent transportation systems (ITS). Based on statistical learning theory, support vector machine (SVM) has better generalization performance and can guarantee global minima for given training data. However, the good generalization performance of SVM highly depends on the construction of kernel function. An effective multi-scale...
Accurate traffic flow forecasting is key to the development of intelligent transportation systems (ITS). The support vector regression (SVR) method is employed for traffic flow forecasting and the comparative results between SVR and BP model using real traffic data of SCOOT system in Dalian city is also presented in this paper. Since support vector machines have better generalization performance and...
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