The applications of data mining technologies in dynamic traffic prediction

One important research field in ITS is traffic flow guidance. To effectively guide the traffic flow, its status must be analyzed and predicted in real-time. This paper presents an analytical and prediction model for urban region traffic flow status, which uses several data mining technologies. With the predicting class neural network, the decision tree constraints set, the association rules constraints set, and the correcting class neural network in the model, we take into consideration the influences on future traffic flow of all factors, not only the traffic flow itself, but also its static and the dynamic indices. Thus it has a great improvement in prediction accuracy.