基于小波变换的城市市区典型路段交通流量预测

提出一种基于"先分-独立预测-再合"思想的新型交通流量预测模型.其应用小波变换技术,对交通流量数据进行分解和重构,将得到的低频概貌信号和高频细节信号,分别用3次平滑指数和ARIMA进行拟合,并应用逐步回归方法建立基于原始交通流量数据,以及高、低频拟合信号的回归方程.对某城市市区典型路段交通流量数据进行验证分析,结果表明,该方程具有较高的拟合精度,优于ARIMA单独使用的效果.

Prediction model of traffic flow along typical roads in city urban districtbased on wavelet transform

A new kind prediction model of traffic flow based on the thought “decomposition-independently predictioncombination”
is described in this paper. First, the traffic flow data are decomposed and reconstructed by using the wavelet
transform technique. And the low frequency outline signal and high frequency detail signal are fitted respectively by using
the three time exponential smoothing method and ARIMA. Then stepwise regression technology is used to establish the
regression equation, in which the primitive traffic flow data are the dependent variable, and high, low-frequency signal’s
fitting data are the independent variables. The confirmation analysis is carried on with traffic flow data from typical roads
in some city urban districts. The results show that the regression equation has a high fitting precision, and is better than the
ARIMA function.