基于小波与混沌集成的短时交通流预测

针对现有短时交通流预测模型的不足,提出了一种用于交通流短时预测的小波与混沌集成方法。首先对交通流序列进行小波分解,分别得到低频部分和高频部分,并在此基础上作进一步分析,结果表明交通流存在混沌特性。然后应用混沌理论分别建立低频部分和高频部分的预测模型,对低频部分和高频部分进行预测。最后应用小波理论对混沌模型预测的结果予以重构,实现对原始交通流序列的预测,与现有方法比较,结果表明该方法具有较高的精度和应用前景。

Research on Wavelet-Chaotic-Based Forecasting of Short-Term Traffic Flow

Aiming at the deficiency of current forecasting of short-term traffic flow,the method of combining wavelet transfor- mation and chaos theory is proposed to model and forecast short-term traffic flow.Firstly,using wavelet decomposition theo- ry,traffic flow series are decomposed respectively 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,using chaos theory,the chaotic forecasting models are established to forecast the low frequency part and the high frequency part respectively.Final- ly,the forecasting result of chaotic model is reconstructed by wavelet theory.By doing so,the forecasting of the original traf- fic flow series can be made.The result demonstrates that this method is of high precision and has extensive potential applica- tions.