Prediction of So2 and Pm Concentration in Coastal Mining Area (zonguldak) with Artificial Neural Network

In this study, artificial neural networks are proposed to predict SO2 and PM concentrations at two different stations in Zonguldak city which is the main coastal mining area in Turkey. The constructed artificial neural network models involve meteorological parameters and historical data on observed SO2, PM as input variables. The models are based on three-layer neural network trained by a back-propagation algorithm. The models accurately match the trend of SO2 and PM concentrations. The results obtained by the proposed models show that the artificial neural network can be used efficiently for analyzing and predicting an efficient air quality.