DocumentCode :
523631
Title :
Cluster Analysis on Urban Rail Transit Ticket Types
Author :
Zhansheng, Wang ; Ling, Ding ; Liqiang, Yang ; Ning, Zhang
Author_Institution :
Gen. Manager´´s Office, Su Zhou Metro Corp., Suzhou, China
Volume :
1
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
950
Lastpage :
953
Abstract :
In order to overcome and optimize the casualness of the traditional urban rail transit ticket type settings. First of all rail transit tickets will be divided into fundamental type and extended type, and on the base of it, the affecting factors of ticket type settings will be discussed; then four clustering variables are selected which include carfare frame consistency, passenger attractiveness, urban traffic coordination and city characteristic consistency, analyze ticket type settings qualitatively, establish the model in accordance with actual survey data of the forthcoming operating rail transit. The example showed that the cluster analysis is a good tools for ticket type classification, and the urban rail transit tickets decision-making model established by cluster analysis method is feasible and effective, which can be set up for the operational decisions such as the ticketing system to provide relevant information.
Keywords :
decision making; pattern classification; pattern clustering; railway engineering; rapid transit systems; socio-economic effects; city transportation; cluster analysis; decision making model; passengers; ticket type classification; urban rail transit ticket types; Automation; Cities and towns; Conference management; Cultural differences; Decision making; Information analysis; Rail transportation; Technology management; Testing; Time measurement; cluster analysis; component; ticket type setting; urban rail transit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.829
Filename :
5522723
Link To Document :
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