Neural networks to predict ozone pollution in industrial areas

In this paper a novel approach, based on a neural network structure, is introduced in order to face with the problem of pollutant estimation in an industrial area. In particular a short-term prediction (six hours ahead) of the O3 pollutant mean value has been performed. The results obtained show the capability of such structures to model complex chemical reactions heavily dependent on the meteorological conditions and on the typical geographical characteristics.