Using ANN and EPR models to predict carbon monoxide concentrations in urban area of Tabriz

ABSTRACT

Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network [AAN] technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression [EPR] model has recently been used as a forecasting tool in some environmental issues. In this research, we compared the ability of these models to forecast carbon monoxide [CO] concentrations in the urban area of Tabriz city