Che Puan, Othman and Roshandeh, Arash Moradkhani and Joshani, Majid (2009) Artificial neural network model of traffic operations at signalized junction in Johor Bahru, Malaysia. In: Proceedings of the 13th WSEAS International Conference on Circuits - Held as part of the 13th WSEAS CSCC Multiconference. World Scientific And Engineering Acad And Soc, Athens, Greece, pp. 219-223. ISBN 978-960474096-3
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Driving behavior models are an important component of microscopic traffic simulation tools. Artificial Neural Networks (ANN) are systems that try to make use of some of the known or expected organizing principles of the human brain. Today neural networks can be trained to solve problems that are difficult for conventional computers or human beings. In this research four signalized junction in Johor Bahru have been considered and simulation of driver's behavior in terms of delay and queue length have been implemented. The neural network approach seems to be more natural and reasonable than the conventional method. The neural network is also more effective and efficient in determining appropriate traffic terms of study.
|Item Type:||Book Section|
|Additional Information:||13th WSEAS International Conference on Circuits - Held as part of the 13th WSEAS CSCC Multiconference; Rodos; 22 July 2009 through 24 July 2009|
|Uncontrolled Keywords:||artificial neural network, delay, flow, queue length, simulation, traffic signal setting|
|Subjects:||T Technology > TJ Mechanical engineering and machinery|
|Deposited By:||Ms Zalinda Shuratman|
|Deposited On:||22 Jul 2011 02:07|
|Last Modified:||22 Jul 2011 02:07|
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