New Artificial Intelligence Modeling for the Photocatalytic Removal of C.I. Acid Yellow 23 in ‎Wastwater

This paper proposes two methods to predict the efficiency of photochemical removal of AY23 by UV/Ag-TiO$_{2}$ process. In this work the potential of the particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) modeling approaches are presented to forecast the photocatalytic removal of AY23 in the presence of Ag-TiO$_{2}$ nanoparticles prepared under desired conditions. To validate the techniques, a total of 100 data are used that randomly splitted in two parts, 80 samples for the training the models and 20 for testing of the models. Experimental results on datasets show that ICA approach is better than PSO approach. Remarkable analysis results reveal that AY23 initial concentration is the most significant factors that influence on the AY23 removal ‎efficiency.‎