Noise prediction in urban traffic by a neural approach

The aim of this paper is to determine functional relationships between the road traffic noise and some physical parameters. Should this goal achieved, it is possible to modify the causes of traffic noise, in order to sensibly reduce it. Correlations are usually derived trough multiple regression analysis. In this paper an alternative solution based on the use of a neural approach is proposed. Its advantage is due to the capability of the neural networks to model non-linear systems such as the one treated in the paper. After an overview about the neural approach, the learning; and production phase results are shown and discussed. They point out how good is the approach proposed to model noise pollution in urban areas.