Prediction LLE data of 2-butanol in the organic phase at various tempratures by GMDH Type- Neural Network

In this study, A GMDH type-neural network was developed to predict LLE data for 2-butanol in the organic phase of ternary system (water + 2-butanol + 2-ethyl-1-hexanol) at various temperatures of 298.2, 308.2, 318.2, and 328.2K and atmospheric pressure. The predicted data were compared with the experimental data which have been previously reported. The average root mean square deviation (RMSD) between the observed and calculated mole fractions was used to reported errors, the estimated/predicted values of GMDH had a good agreement with experimental data

Keywords:

Liquid-liquid equilibrium , GMDH type neural network , ternary system , 2-butanol , pareto