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《Control and Decision》 2009-08
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Traffic network flow forecasting based on switching model

CHEN Yue-ming,XIAO De-yun(Department of Automation,Tsinghua University,Beijing 100084,China.)  
For the nonlinearity of complicated urban traffic flow,a switching autoregressive integrated moving average(ARIMA) model is proposed and employed to explore how traffic flow varies with time,so that accurate predictions can be obtained.The turning proportion matrix is introduced to describe the traffic network states.Considering the difference characters of the turning proportion matrix between congestion case and discongestion case,two formulas are proposed to forecast the network traffic flow.The simulation results show the effectiveness and feasibility of the proposed approach.
【Fund】: 国家“十五”科技攻关项目(2005BA414B09);; 国家“十一五”科技支撑项目(2007BAK12B15)
【CateGory Index】: U491.112
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