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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15472
Title: Artificial neural network modeling for road traffic noise prediction
Authors: Kumar K.
Parida, Manoranjan
Katiyar V.K.
Published in: Proceedings of 2012 3rd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2012
Abstract: Several attempts have been made by the researchers to predict and model urban road traffic noise mathematically and statistically. There has been a lot of interest in the new techniques for analyzing data. Neural networks offer a new strategy with enormous potential for many tasks in the domain of geospatial planning. ANN technique for modeling provides smaller errors in comparison to other classical methods. Neural networks have been applied to many interesting problems in various areas including road traffic noise prediction. In the present study an attempt has been made to explore the application of neural networks to road traffic noise prediction in Lucknow city, capital of Uttar Pradesh, India. Traffic volume, speed and noise level data were collected at ten selected locations. For development of model, classified traffic volume (Car/Jeep/Van, Scooter/ Motorcycle, LCV/ Minibus, Bus, Truck and 3-Wheeler), traffic speed on both sides of the road were taken as input data. Output was estimated as Leq. Performance of the model was tested by root mean square error (RMSE), mean absolute error (MAE) and coefficient of correlation (R). It was observed that there is no significant difference between observed and predicted noise levels in the present case, indicating the accuracy of model. ¬© 2012 IEEE.
Citation: 2012 3rd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2012, (2012), (): -
URI: https://doi.org/10.1109/ICCCNT.2012.6395944
http://repository.iitr.ac.in/handle/123456789/15472
Issue Date: 2012
Keywords: ANN (artificial neural network)
Leq
noise prediction
Urban noise
Author Scopus IDs: 55578633100
8963649200
6603690424
Author Affiliations: Kumar, K., Department of Mathematics, Indian Institute of Technology, Roorkee-247667, India
Parida, M., Department of Mathematics, Indian Institute of Technology, Roorkee-247667, India
Katiyar, V.K., Department of Civil Engineering, Indian Institute of Technology, Roorkee-247667, India
Corresponding Author: Kumar, K.; Department of Mathematics, Indian Institute of Technology, Roorkee-247667, India
Appears in Collections:Conference Publications [CE]

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