Study of Dynamic Adsorption from Wastewater into Mineral Activated Carbon Using Artificial Neural Network

Water bodies are the most common natural resources that have been contaminated as a result of different human activities. Actually, in industries various methods of treatment of wastewater and many adsorbent materials used for purification of effluents have existed. An artificial neural network (ANN) was used in this study to predict the removal of sodium decanesulfonate using actived carbon obtained by the calcination of mineral biomass under different conditions. The structure of [3-3-1] was obtained and given a good correlation coefficient (R2 = 0.9965) with root mean squared error (RMSE = 0.0276). For the stage of interpolation and extrapolation, the results present a high correlation coefficient close to 1 which provides the robustness and the high capacity of ANN developed model.