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Centrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka.

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dc.contributor.author Jayaweera, I.M.L.N.
dc.contributor.author Perera, K.K.K.R.
dc.contributor.author Munasinghe, J.
dc.date.accessioned 2017-12-13T04:24:38Z
dc.date.available 2017-12-13T04:24:38Z
dc.date.issued 2017
dc.identifier.citation Jayaweera,I.M.L.N., Perera, K.K.K.R.,and Munasinghe, J. (2017). Centrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka. IOSR Journal of Mathematics (IOSR-JM), Department of Mathematics, Faculty of Science, University of Kelaniya, Sri Lanka.p.13. en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/18523
dc.description.abstract This study presents a graph theoretical approach to identify the traffic congestion on a road network. Problem address on a city called Kiribathgoda situated in the western province of Sri Lanka. In the analysis of social networks, centrality measures played a vital role to identify the central nodes in a given network. We look at the applicability of centrality and betweenness measures in order to identify the most important locations which directly affect to the traffic congestion in road networks in Sri Lanka. Using the graph theoretical approach a traffic network for a selected area was constructed and several centrality measures were calculated. According to our simulation results, it was noted that the practically identified locations could be identified from the simulations carried out using the centrality measures. en_US
dc.language.iso en en_US
dc.publisher IOSR Journal of Mathematics (IOSR-JM), Department of Mathematics, Faculty of Science, University of Kelaniya, Sri Lanka. en_US
dc.subject Centrality Measures en_US
dc.subject Betweenness Measures en_US
dc.subject Road Network en_US
dc.subject Graph en_US
dc.subject Traffic en_US
dc.title Centrality Measures to Identify Traffic Congestion on Road Networks: A Case Study of Sri Lanka. en_US
dc.type Article en_US


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