Predicting traffic induced noise using artificial neural network and multiple linear regression approach

Urban noise pollution has risen to the top of the list of issues related to the human health in recent years. Automobiles are the primary source of noise in cities. The noise analysis has been carried out on the busy streets of Ahmedabad, Gujarat's commercial hub and the state's most populous city. This research proposed a model using soft computing approach, artificial neural networks (ANN), for the prediction of environmental urban noise. The ANN technique was applied on the collected data which is chosen streets in an urban region. The outcomes were compared to the multilinear regression model (MLR). According to the study, the ANN system is able to forecast urban noise with better mean square error (MSE) of 5.4 as compared to MSE of 9.30 forecasted by MLR.