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Traffic Generation Model for Delhi Urban Area Using Artificial Neural Network

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Author(s): Shivendra Goel | J. B. Singh2 | Ashok Kumar Sinha

Journal: BVICAM's International Journal of Information Technology
ISSN 0973-5658

Volume: 2;
Issue: 2;
Date: 2010;
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Keywords: ANN - Artificial Neural Network.

ABSTRACT
Transport facility and socio-economic structure for a city are interdependent resulting into improved transport infrastructure, which in turn influences socio-economic growth. As the society evolves it generates transport demand. The classical transportation planning methods are based on simple extrapolation of trends. Some mathematical models like linear regression models have also been used by researchers for estimating traffic generation for future period, however, these models do not account for nonlinearly in the model. In the present paper Artificial Neural Network Model has been used in modal Traffic Generation in Delhi Urban Area .ANN models account for nonlinear relationship between independent variables and the dependent variables. Future estimates of percentage of traffic generation by cars, buses and smaller vehicles in the inner, middle and outer areas of urban Delhi have been derived using the ANN. The model is implemented on MATLAB and the error in the training phase of ANN is quite low.
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