DocumentCode :
501338
Title :
Research on Railway Passenger Traffic Volume Forecasting Method
Author :
Changqing, Zeng ; Chengzhi, Long
Author_Institution :
Comput. Technol. Eng. Res. Inst., Nanchang Univ., Nanchang, China
Volume :
1
fYear :
2009
fDate :
15-17 May 2009
Firstpage :
279
Lastpage :
282
Abstract :
Railway passenger traffic volume forecasting is an important responsibility of the railway transportation management departments, railway passenger traffic volumes are influenced by multiple factors, and the action mechanisms of these factors are usually unable to be described by accurate mathematical linguistic forms, so the theory and method of railway passenger traffic forecasting remain a focus in research all the time. The paper analyzes data using rough set theory. Combining rough set theory and the characteristics of railway passenger traffic volume data, we bring forward a forecasting model of railway passenger traffic volume using rough set theory. Through setting up, hybrid clustering method of discretization and reduction decision table, a rule set concerning forecasting of railway passenger traffic volumes is achieved - rough set forecasting model.
Keywords :
railways; rough set theory; hybrid clustering method; railway passenger traffic volume forecasting method; railway transportation management; rough set theory; Application software; Demand forecasting; Economic forecasting; Information systems; Information technology; Predictive models; Rail transportation; Rough sets; Set theory; Traffic control; Discretization; Forecasting model; Rough set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
Type :
conf
DOI :
10.1109/IFITA.2009.555
Filename :
5231596
Link To Document :
بازگشت