Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/5028
Title: An apporach for analyzing queuing systems using Markov chain Monte Carlo methods: A traffic flow case study
Authors: Wong, X.C. 
Ahmed, S.K. 
Zulkifli, F. 
Ramasamy, A.K. 
Issue Date: 2009
Journal: SCOReD2009 - Proceedings of 2009 IEEE Student Conference on Research and Development 2009, Article number 5443360, Pages 41-44 
Abstract: In our urban community, having to wait In line Is a dally nuisance as precious time Is wasted. One simple example Is traffic congestion on roads. Reduction of these congestions will not only minimize time wastage but also lead to a healthier life. For this reason, various approaches have been taken to mitigate this problem. In this paper, a simulation approach is proposed to model and investigate the behavior of traffic flow on roads. This is due to the difficulty in obtaining exact solutions based on probability theory and queuing systems even for moderately complex systems. In this paper, the simulation technique used is based on the Markov Chain Monte Carlo technique. It is noticed that the result obtained shows that traffic behavior can be modeled accurately. Thus, this simple approach can be extended to other similar systems such as computer networks, communication systems, etc. ©2009 IEEE.
DOI: 10.1109/SCORED.2009.5443360
Appears in Collections:COE Scholarly Publication

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