e-ISSN : 0975-3397
Print ISSN : 2229-5631
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ABSTRACT

Title : Implementation of Neural Network with a variant of Turing Machine for Traffic Flow Control
Authors : Rashmi Sehrawat, Honey Malviya, Vanditaa Kaul
Keywords : Intelligent Traffic Flow Control, Turing Machine, Neural Network, Multilayer Feed-forward Neural Network, Sigmoid Activation Function.
Issue Date : May 2013.
Abstract :
The conventional method of operation of a typical traffic light is to distribute the time equally for all the directions.This method causes congestion when throughput of the signal increases and is also ineffective in managing traffic flow. In this paper, we have proposed a new model for managing traffic intelligently.The model is based on Turing machine with the application of neural network. The model considers current traffic status of its own signal along with the status of its adjacent signals to determine the ratio of time slot for each signal therefore, reducing traffic congestion to a greater extent and ensuring steady flow of traffic in a wide region.
Page(s) : 343-348
ISSN : 0975–3397
Source : Vol. 5, Issue.05

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