Title :
The improvement of the forecasting model of short-term traffic flow based on wavelet and ARMA
Author :
Zheng, Cao ; Li, Lei
Author_Institution :
Dept. of Traffic & Transp., Beijing Jiaotong Univ., Beijing, China
Abstract :
Currently, the effects of accidental factors are not considered while the bad and missing data are in the data processing of forecasting traffic flow. In the paper the forecasting model of short-term traffic flow based on wavelet and ARMA is improved by processing data with exponential smoothing (ES). And compared with the traditional model, the new model improves the prediction precision and provides a guideline for forecasting the traffic flow.
Keywords :
autoregressive moving average processes; traffic control; transportation; wavelet transforms; ARMA; accidental factor; data processing; exponential smoothing; forecasting model; prediction precision; wavelet based short term traffic flow; Biological system modeling; Data models; Forecasting; Predictive models; Roads; Smoothing methods; Wavelet transforms; ARMA; forecast; traffic jlmvt; wavelet;
Conference_Titel :
Supply Chain Management and Information Systems (SCMIS), 2010 8th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-962-367-696-0
