Neda Mohebbi - Geology Sience Department, Payam Noor University of Asadabad, Hamadan, Iran
Armin Mohebbi - Chemical Engineering Department, Amirkabir University of Technology, Tehran, Iran
Maryam Ahmadi pour - Department of Gas Engineering, Ahwaz Faculty of Petroleum, Petroleum University of Technology, Ahvaz, Iran

This study presents the use of multilayer perceptron neural network (MLP-NN) for estimation of the amount of equilibrium sulfur adsorption in liquid phase of hydrocarbon/ sulfur compound solution. The model was precisely developed on a collection of ۱۰۷ experimental data of seven types of sulfur compounds. Developed Model account for the effect of inputs parameters, including initial sulfur concentration, adsorbent weight, solvent/ solute molecular weights, solvent/ solute densities, adsorbent particle size, temperature and Si/ Al ratio of adsorbent. Admittedly the amount of equilibrium sulfur adsorption was assumed as the only output. Graphical presentations and statistical comparisons were applied to analyze the performance and accuracy of developed model. Results indicate that MLP-NN model provide precise predictions. Developed model offers fair agreement in predictions of the adsorption experimental data points with average absolute relative deviation and overall R۲ values of ۱.۴۳% and ۰.۹۹۹۶ respectively.

Sulfur adsorption; Prediction; MLP-NN; Model