Amaury de Souza, Flavio Aristones and Fabio Verissimo Goncalves
The estimative of the concentration of surface ozone promotes the creation of data for planning forecasting the air quality, useful in the management of public health. The aim of this study was to develop an Artificial Neural Network (ANN) to estimate the concentration of surface ozone due to climate data daily. The ANN, the Feedforward Multilayer Perceptron kind, was trained taking as reference the daily concentration of ozone measured. In the intermediate and output layers we used activation functions type tan-sigmoid and linear, respectively. The performance of the ANN developed was very good, and it can be considered as part of the set of indirect methods to estimate the concentration of surface�ozone. The proposed model can be used by the government as a tool to enable the public interventional actions during the period of atmospheric stagnation, when ozone levels in the atmosphere may represent risks to public health.