Modeling Environmental Noise Using Artificial Neural Networks

Abstract

Since 1972, when the World Health Organization (WHO) classified noise as a pollutant, most industrialized countries have enacted laws or local regulations that regulate noise levels. Many scientists have tried to model urban noise, but the results have not been as good as expected because of the reduced number of variables. This paper describes artificial neural networks (ANN) to model urban noise. This model was applied to data collected at different street locations in Granada, Spain. The results were compared to those obtained with mathematical models. It was found that the ANN system was able to predict noise with greater accuracy, and therefore it was an improvement on these models. Furthermore, this paper reviews literature describing other research studies that also used soft computing techniques to model urban noise.