Wavelet-Chaotic Integration-Based Forecasting for Short-Term Traffic Flow

Based on the theory of wavelet transformation and chaos integration, a method is put forward to model and forecast short-term traffic flow. Firstly, using wavelet decomposition theory, traffic flow series are decomposed into two parts: the low frequency part and the high frequency part. And the further analysis of decomposition indicates that a chaos feature exists in the traffic flow. Secondly, by using chaos theory, the chaotic forecasting models are established to forecast the low frequency part and the high frequency part. Finally, wavelet theory is used to reconstruct the forecasting result of chaotic model. By doing so, the forecasting of the original traffic flow series can be done. The result demonstrates that the method is of high precision and has extensive potential applications.