Research on prediction of the short-term traffic flow based on cloud model
Jianmin Xu · Jisuanji gongcheng yu sheji · 2012
In order to improve the prediction precision of the short-term traffic flow,a prediction method of short-term traffic flow based on cloud model is proposed by artificial intelligence with uncertainty.The traffic flow is fit by cloud model.The historical cloud and the present cloud are built by historical traffic flow and present traffic flow.The forecast cloud is produced by both clouds.Then,combining with the volume of the short-term traffic flow of an intersection in Guangzhou city,the model is calculated and simulated through programming.Max absolute error(MAE) and mean absolute percent error(MAPE) are used to estimate the effect of prediction.The simulation results indicate that this prediction method is effective and advanced.The change of the historical and real time traffic flow is taken into account in this method.Because the short-term traffic flow is dealt with as a whole,the error of prediction is avoided.The prediction precision and real-time prediction are satisfied.