Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/13624
Title: Modeling and Simulation of Road Traffic Noise Using Artificial Neural Network and Regression
Authors: M. Honarmand
S. M. Mousavi
Keywords: Artificial neural network
road traffic noise
regression
modeling
simulation
Issue Date: 2014
Publisher: Journal of Environmental Science and Engineering
Abstract: Modeling and simulation of noise pollution has been done in a large city, where the population is over 2 millions. Two models of artificial neural network and regression were developed to predict incity road traffic noise pollution with using the data of noise measurements and vehicle counts at three points of the city for a period of 12 hours. The MATLAB and DATAFIT softwares were used for simulation. The predicted results of noise level were compared with the measured noise levels in three stations. The values of normalized bias, sum of squared errors, mean of squared errors, root mean of squared errors, and squared correlation coefficient calculated for each model show the results of two models are suitable, and the predictions of artificial neural network are closer to the experimental data.
URI: http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/13624
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