基于小波消噪和混沌时间序列的交通流预测研究

基于实际交通流变化的不确定性和交通系统时变复杂的特征,应用小波分析理论,对原始交通流数据进行消噪处理,使消噪后的数据更能反映交通流的本质及变化规律。再针对交通流的非线性特征及其短期可预测性,应用混沌时间序列预测模型来预测短时交通量。结果表明:先进行小波消噪再进行预测所得的结果与实测值有更高的拟合度,可以用于短时交通流的预测。

The Traffic Flow Prediction Based on Wavelet De-noising and Chaotic Time Series Theory

Based on the analysis of the characteristics of nonlinearity and strong interference of traffic flow to the complex and uncertainty of time variance in real traffic system,a new approach was proposed for traffic flow prediction.First,wavelet transform is employed to eliminate the noise of original traffic data to reflect the essence and variation of traffic flow.According to the nonlinearity and predictability in short time of traffic flow,a chaotic time series model was applied to forecast traffic flow wit...