Application of an artificial neural network on railway passenger flow prediction

Author

Dan Zheng ; Yao Wang

Author_Institution

Sch. of Software, East China Jiaotong Univ., Nanchang, China

Volume

1

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

149

Lastpage

152

Abstract

This paper applies the theory of data warehouse and data mining and its derived technology to deal with the huge amount of data of the Ticket Selling and Reserving System of Chinese Railway (TRS). We use effective data mining in passenger flow analysis to establish a logical forecasting and analysis model. Our model can provide accurate decision-making information and an advanced way of forecast for the railway transit authority to make a optimal planning for passenger transport, scientific organization of the railway system and high efficiency of transport energy.

Keywords

data mining; data warehouses; neural nets; railways; Chinese railway passenger flow prediction; artificial neural network; data mining; data warehouse; decision-making information; passenger flow analysis; passenger transport; railway system scientific organization; railway transit authority; ticket selling and reserving system; transport energy; Biological neural networks; Data mining; Forecasting; Neurons; Predictive models; Rail transportation; Training; BP neural network; data mining; data warehouse;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on

Conference_Location

Harbin, Heilongjiang, China

Print_ISBN

978-1-61284-087-1

Type

conf

DOI

10.1109/EMEIT.2011.6022884

Filename

6022884