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Research on Forecasting Model in Short Term Traffic Flow Based on Data Mining Technology

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5 Author(s)
Bin-sheng Liu ; Sch. of Manage., Harbin Inst. of Technol. ; Yi-Jun Li ; Hai-Tao Yang ; Xue-sheng Sui
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Accurate forecasting in short term traffic flow is of vital importance in management of good road traffic. In order to increase the precision, this paper proposes a forecasting model in short term traffic flow based on data mining technology. The model consists of three stages: first, the rough set theory and the genetic algorithm are applied to select relevant forecasting variable to the traffic flow; second, training pattern of wavelet neural network which is similar to the forecast term is carried out by using data mining technology; finally the wavelet neural network is used to carry on forecasting the traffic flow. Through forecasting traffic flow at Xinhua Street in Huhehot, the result shows that this model has a higher precision and surpasses gray GM (1, 1) and the BP artificial neural network model, which provides a new reliable and effective way of forecasting short term traffic flow of nodes in urban road network

Published in:

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on  (Volume:1 )

Date of Conference:

16-18 Oct. 2006

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