Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis

Directed graphs; Landforms; Central business districts; Public transportation; Rail networks; Temporal analysis; Transportation planning; Travel patterns; Travel routes; Tourism industry

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Bibliographic Details
Main Authors:	Hafiz Bin Yaacob M.N., Zuhri Bin Zuhud D.A., Magalingam P., Maarop N., Samy G.N., Shanmugam M.
Other Authors:	57220804522
Format:	Conference Paper
Published:	Institute of Electrical and Electronics Engineers Inc. 2023
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Institution:	Universiti Tenaga Nasional

id	my.uniten.dspace-25341
record_format	dspace
spelling	my.uniten.dspace-253412023-05-29T16:08:20Z Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis Hafiz Bin Yaacob M.N. Zuhri Bin Zuhud D.A. Magalingam P. Maarop N. Samy G.N. Shanmugam M. 57220804522 57220807256 35302809600 45661569600 35303350500 36195134500 Directed graphs; Landforms; Central business districts; Public transportation; Rail networks; Temporal analysis; Transportation planning; Travel patterns; Travel routes; Tourism industry As the population grows, the importance of public transportation increased rapidly as people can use them to travel within the city or town easily. Due to the immense complexity of any public rail, a rich set of information can be uncovered and mined using Social Network Analysis (SNA). In this research, SNA is used to analyse Klang Valley's rail network and its daily riders' pattern. Klang Valley's rail network serves the area of Klang Valley and Greater Kuala Lumpur with the length of 555.7KM. SNA is a type of analysis that characterizes any phenomena within entities' relationships based on their source and destination. A directed graph was constructed based on a dataset consisting of riders' travel history containing 120 nodes and 5567 edges; the nodes represent stations and the edges are daily-commuters' travel routes between various stations. Temporal analysis is then performed on the dataset to understand the travel trends of residential and central business district (CBD) stations during peak and non-peak hours. Another analysis was also done to identify the rails' network performance when handling attacks on high degree stations; its robustness is also studied. It is found that Klang Valley's rail network is highly robust with more than 500 triad connection detected, ensuring it to recover easily if either one station fails. This research helps to provide new insight into future transportation planning and rail network traffic scheduling. � 2020 IEEE. Final 2023-05-29T08:08:19Z 2023-05-29T08:08:19Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243547 2-s2.0-85097642649 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097642649&doi=10.1109%2fICIMU49871.2020.9243547&partnerID=40&md5=42f51591bc28ba7280d778be06cd6178 https://irepository.uniten.edu.my/handle/123456789/25341 9243547 183 188 Institute of Electrical and Electronics Engineers Inc. Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
description	Directed graphs; Landforms; Central business districts; Public transportation; Rail networks; Temporal analysis; Transportation planning; Travel patterns; Travel routes; Tourism industry
author2	57220804522
author_facet	57220804522 Hafiz Bin Yaacob M.N. Zuhri Bin Zuhud D.A. Magalingam P. Maarop N. Samy G.N. Shanmugam M.
format	Conference Paper
author	Hafiz Bin Yaacob M.N. Zuhri Bin Zuhud D.A. Magalingam P. Maarop N. Samy G.N. Shanmugam M.
spellingShingle	Hafiz Bin Yaacob M.N. Zuhri Bin Zuhud D.A. Magalingam P. Maarop N. Samy G.N. Shanmugam M. Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
author_sort	Hafiz Bin Yaacob M.N.
title	Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
title_short	Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
title_full	Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
title_fullStr	Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
title_full_unstemmed	Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis
title_sort	identifying the klang valley rail riders' travel pattern for future expansion using social network analysis
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2023
_version_	1806427524853399552

Identifying the Klang Valley Rail Riders' Travel Pattern for Future Expansion using Social Network Analysis

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