The traditional forecasting methods are not suitable for short term traffic flow prediction, due to strong non-linear, time varying characteristics of urban transportation system. In order to improve forecasting accuracy of short term traffic flow, short term traffic flow prediction model based on support vector machine is presented. The most important parameter of support vector machine is parameter selection including the kernel function parameter and the penalty factor, which has significant influence on the properties of model prediction. P...
