a Daghbandan - Assistant Professor, Department of chemical engineering, Faculty of Engineering, University of Guilan
h Ghanadzadeh - Professor, Department of chemical engineering, Faculty of Engineering, University of Guilan
m Akbari Zadeh - Phd Student, Department of chemical engineering, Faculty of Engineering, University of Guilan

ANFIS and GMDH type Neural Networks (NN) employing the Pareto design were used to predict ternary systems (water,phosphoric acid, Isoamyl acetate) LLE data, for which the experimental LLE data and application of some thermodynamic models such as UNIQUAC were reported previously by some of the authors. Experimental data were divided to two set: Training and Testing sets. To measure the goodness of present model, four statistical parameters were introduced as objective functions and multi-objective evolutionary optimization algorithm was employed. The performance and reliability of this type of networks was successfully approved for considered systems based on the obtained results and good agreements were found between experimental and predicated data

liquid- liquid extraction, Ternary System, pareto, SNE, ANFIS, MUGA