Research on Short-Term Traffic Flow Combined Forecasting Based on Wavelet Package and Least Square Support Vector Machines

Because wavelet is suitable for processing nonlinear,random signals and support vector machines excel at solving less-data,nonlinear,multi-dimension problems,the paper proposes combining of wavelet package with least squares support vector machines for short-term traffic flow forecasting.First,theories of wavelet package and least squares support vector machines are introduced,and then a short-term traffic flow forecasting method based on wavelet package and least squares support vector machines is proposed.Second,the effect of the method is tested by the real-time traffic flows collected in Beijing City.The result shows the feasibility and validity of the proposed method.