Technical Program

Paper Detail

Session:Networks and Communication Systems Modeling
Time:Tuesday, May 18, 16:30 - 16:50
Presentation: Lecture
Topic: Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps.
Authors: Guoqiang Yu; Tsinghua University 
 Changshui Zhang; Tsinghua University 
Abstract: Switching dynamic linear models are commonly used methods to describe change in an evolving time series, where switching ARIMA model is a special case. Short-term forecasting of traffic flows is an essential part of Intelligent Traffic Systems (ITS). In this paper, we apply switching ARIMA model to traffic flow series. We have observed that the conventional switching model is inappropriate to describe the pattern changing. Thus the variable of duration is introduced and we use the sigmoid function to describe the influence of duration to the transition probability of the patterns. Based on the switching ARIMA model, the forecasting algorithm is presented. We apply the proposed model to the real data obtained from UTC/SCOOT systems in Traffic Management Bureau of Beijing. The experiments show that our proposed model is applicable and effective.

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