LLE data are important for simulation and design of extraction equipment. In this study, deep neural network (DNN) structure was proposed for modelling of the ternary liquid-liquid equilibrium (LLE). LLE data of (water + butyric acid + 5-methyl-2-hexanone) ternaries defined at three different temperatures of 298.2, 308.2, and 318.2 K and P = 101.3 kPa, were obtained experimentally and then correlated with nonrandom two-liquid (NRTL) and universal quasi-chemical (UNIQUAC) models. The performance ...