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2017 ◽  
Vol 56 (9S) ◽  
pp. 09NA03
Author(s):  
Norihiko Ishii ◽  
Yutaro Katano ◽  
Tetsuhiko Muroi ◽  
Nobuhiro Kinoshita

2013 ◽  
Vol 409-410 ◽  
pp. 1315-1319 ◽  
Author(s):  
Yan Hui Wang ◽  
Jun Jin ◽  
Man Li

Facing the typical big city is into the network operation ,currently, it brings some difficulties without the section traffic data obtained in real time to monitor and limit measures. To solve the problem, this paper adopts the second exponential smoothing models based on the historical data at the same period, and forecasts the subway section passenger flow. In this paper, the data is collected a section traffic in Beijing Subway from every Monday to every Friday in March 2013, and the former periods are used as the sample data, and predicts the last day, and compares them with the known data to check error. The result shows the method has a strong practical utility.


2009 ◽  
Vol 18 (10) ◽  
pp. 4154-4160 ◽  
Author(s):  
Li Yuan ◽  
Zeng Gui-Hua ◽  
Moon Ho Lee

2003 ◽  
Author(s):  
Jingfeng Liu ◽  
Hongwei Song ◽  
B. V. K. Vijaya Kumar

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