Forecasting Model of Traffic Flow Prediction Model Based on Multi-resolution SVR

Abstract

Based on wavelet decomposition and phase space reconstruction, proposed a multi-resolution SVR traffic flow prediction model. The complex traffic flow sequence is transformed into a single character at different scales by wavelet transform, and the sub-sequences of different scales are predicted by the SVR model respectively. To extract more key information from the time series, according to the chaotic characteristics of traffic flow, phase space decomposition is performed to improve prediction accuracy. Experiments show that the proposed method can better reflect the sequence details and variation characteristics and achieve higher prediction accuracy.