PSO and NN modeling for photocatalytic removal of pollution in wastewater

Abstract

This paper discusses the elimination of C.I. Acid Yellow 23 (AY23) using UV/Ag-TiO 2 process. To anticipate the photocatalytic elimination of AY23 with the existence of Ag-TiO 2 nanoparticles processed under desired circumstances, two computational techniques namely neural network (NN) and particle swarm optimization (PSO) modeling are developed. A summed up of 100 data are used to establish the models, wherein introductory concentration of dye, UV light intensity, initial dosage of nano Ag-TiO 2 and irradiation time are the four parameters applied as the input variables and elimination of AY23 as output variable. The comparison of the predicted results by designed models and the experimental data proves that the performance of the NN model is comparatively sophisticated than the PSO model.