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- W593632135 abstract "Regarded multi-spot road traffic state as research object, a method of road traffic state multi-spot time series forecasting based on state space model was proposed and road traffic state forecasting was extended from single-spot forecasting to multi-spot forecasting.Firstly,using road traffic state multi-spot time series data,multidimensional auto-regressive model was established and converted to format of state space model,then,EM algorithm was used to estimate the state space model parameters in order to establish state space model of multi-spot traffic state.Secondly,system state was estimated based on time series data,then,Kalman filtering method was used to perform one-step prediction and simultaneously new data was supplied to update system state so as to perform next prediction.In the way,prediction was performed on and on.Finally,the effect of proposed method was tested by multi-spot time series data collected by six traffic detectors on certain urban expressway and was compared with forecasting method of single-spot Kalman filtering.The result shows that the proposed model is feasible and effective." @default.
- W593632135 created "2016-06-24" @default.
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- W593632135 date "2007-07-01" @default.
- W593632135 modified "2023-09-23" @default.
- W593632135 title "Road Traffic State Multi-spot Time Series Forecasting Based on State Space Model" @default.
- W593632135 hasPublicationYear "2007" @default.
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