ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)
|Session 4: Information Theory and Information Systems
|05 September 2017
Short-term Forecast Model of Vehicles Volume Based on ARIMA Seasonal Model and Holt-Winters
1 Intelligent Center, Yunnan Science Research Institute of Communication & Transportation, Kunming, China
2 National Pilot School of Software, Yunnan University, Kunming, China
In order to alleviate the urban traffic congestion and ensure traffic safety, we need to do a good job in urban road traffic safety planning, make the real-time analysis and forecast of urban traffic flow to detect changes of current traffic flow in time, make scientific planning of roads and improve the road service ability and the transport efficiency of freight vehicles. The data of short-term vehicles volume is characterized by uncertainty and timing correlation series. Given this, the ARIMA seasonal model and the Holt-Winters model are used to establish a forecasting model for the short-term vehicles volume of the city. Finally, we compare the model with predictions.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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