DocumentCode
497428
Title
Study on Bus Passenger Capacity Forecast Based on Regression Analysis including Time Series
Author
Sun Wen-xia ; Song Ti ; Zhong Hai
Author_Institution
Sch. of Manage., Tianjin Univ., Tianjin, China
Volume
2
fYear
2009
fDate
11-12 April 2009
Firstpage
381
Lastpage
384
Abstract
The passenger capacity in public transit is important to urban road and transportation planning. Passenger volume is influenced by multiple factors and unable to be described with accurate mathematical models. Regression analyses predict and time-series data analysis for forecasting are two important prediction models. These two models have characteristics of each. In this paper, time-series data was blend into regression analyses predict. Integrated the two forecasting methods, this paper combined the merits between them. Bus passenger capacity forecast model based on regression analysis including time series is put forward in this paper. This model better reflects the practical condition of bus passenger. The model passes through all tests. By analyzing the historic data of passenger volume of Xipsilaan, we study on bus passenger capacity forecast based on regression analysis including time series. The new model is fitting practical data more preferable.
Keywords
forecasting theory; regression analysis; road vehicles; time series; transportation; bus passenger capacity forecasting; data analysis; mathematical model; prediction model; public transit; regression analysis; time series; transportation planning; urban road planning; Capacity planning; Data analysis; Predictive models; Regression analysis; Road transportation; Technology forecasting; Time measurement; Traffic control; Urban planning; Yttrium; least squares technique; prediction; regression analysis; time-series data; transit traffic;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-0-7695-3583-8
Type
conf
DOI
10.1109/ICMTMA.2009.268
Filename
5203452
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