Prediction of SO2 and PM concentrations in a coastal mining area [Zonguldak, Turkey] using an artificial neural network

Abstract

In this study, artificial neural networks are proposed to predict the concentrations of So and PM at two different stations in zonguldak city, a major coastal mining area in Turkey. The established artificial neural network models involve meteorological parameters and historical data on observed So 2 , PM as input variables. The models are based on a three-layer neural network trained by a back-propagation algorithm. The models accurately measure the trend of sO 2 and PM concentrations. The results obtained through the proposed models show that artificial neural networks can efficiently be used in the analysis and prediction of air quality.