DocumentCode :
2541395
Title :
Optimization of Rail Transit Departure Frequency Based on Fuzzy Clustering - Take Shanghai Rail Transit Line 9 for Example
Author :
Zhong, Wu ; Hanwei, Li
Author_Institution :
Coll. of Manage., Shanghai Univ. of Eng. & Sci., Shanghai, China
fYear :
2012
fDate :
12-14 Oct. 2012
Firstpage :
875
Lastpage :
877
Abstract :
This article takes example of Shanghai Rail Transit Line 9, and uses fuzzy clustering method to classify passenger flow in different periods of the working and non-working days by MATLAB program. Full-day time intervals are divided into five categories, and we optimize the departure frequency based on the five categories. This optimization method improves the operational efficiency of urban railway transport, and reduces the cost of it. The method of research is innovative, and research findings are instructive in practice.
Keywords :
fuzzy set theory; pattern clustering; rail traffic; MATLAB program; Shanghai rail transit line 9; cost reduction; fuzzy clustering method; nonworking days; operational efficiency improvement; passenger flow classification; rail transit departure frequency optimization; time intervals; urban railway transport; working days; Cities and towns; Educational institutions; MATLAB; Optimization; Rail transportation; Rails; Time frequency analysis; departure frequency; fuzzy clustering; passenger flow; time intervals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Business Computing and Global Informatization (BCGIN), 2012 Second International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-4469-2
Type :
conf
DOI :
10.1109/BCGIN.2012.233
Filename :
6382674
Link To Document :
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