Modeling of Arsenic (III) Removal by Evolutionary Genetic Programming and Least Square Support Vector Machine Models

Abstract

In this study, the co-precipitation method was used to synthesize the cerium oxide tetraethylenepentamine (CTEPA) hybrid material with the variation of the molar concentration of the metal oxide. Physicochemical techniques, like FESEM, XRD, FTIR, HR-TEM and TGA-DSC, were used to characterize the hybrid material. The adsorption experiment was carried out to estimate the optimum condition for adsorption with the variation of adsorbent dose, pH of the solution, time and initial concentration of the adsorbate. These variables are further used to develop an approach for the evaluation of As(III) removal from water by using evolutionary genetic programming techniques (GP) and least square support vector models (LS-SVM). GP model was found to be the best performing model for understanding the nonlinear behavior and prediction of As(III) removal (minimum standard error GPtraining 0.411, GPtesting 0.658). The adsorption process in this study followed second order kinetics. The experimental data were best fitted to linearly transformed Langmuir isotherm with an R2 (correlation coefficient) value of >0.99 and having a maximum adsorption capacity of 124.8 mg/g at 25 ± 2 °C. The type of adsorption process was derived from the Dubinin-Radushkevich isotherm model. A comparison between the model and actual experimental values gave a high correlation coefficient value (R2training (GP) 0.988, R2testing (GP) 0.977).