Short-Term Highway Traffic Flow Forecasting Based on XGBoost

摘要

With the rapid development of urban intelligent transportation system, the prediction short-term of traffic flow attracts more and more attention. As the lack of the characteristics of traffic flow and appropriate models, the accurate predction of the traffic flow are facing a big challenge. A short-term traffic flow prediction model based on extreme gradient rise is proposed in this paper. The experiment results reveal the superiority of the modle by comparing with the traditional prediction model.