STATISTICAL MODELLING IN ECOLOGICAL MANAGEMENT USING THE ARTIFICIAL NEURAL NETWORKS (ANNs)

This paper presents the results of modeling the sulfur dioxide (SO2) emission in the vicinity of the copper-smelting complex according to the technological and meteorological parameters. As the part of the technological project with an environmental impact, for the prediction of potential SO2 emission, Artificial Neural Networks (ANNs) were used as the modelling tool. Input parameters of the model included technological data: amount of sulfur introduced to the reverberatory furnace with the charge and the amount of sulfur removed from the process gas in the sulfuric acid factory. Meteorological parameters included: wind speed and wind direction, air temperature, humidity and barometric pressure. Also, the influence of the season was considered as well as the location of the measuring point and its distance from the factory chimneys. The results obtained indicated that the artificial neural networks could be successfully used for prediction of the sulfur dioxide emission according to the known technological and meteorological parameters.