TY - JOUR ID - 7197 TI - Applying Pareto Design of GMDH-Type Neural Network for Solid-Liquid Equilibrium of Binary Systems (Isotactic Poly 1-Butene (1)-Organic Solvents (2)) JO - Iranian Journal of Chemistry and Chemical Engineering JA - IJCCE LA - en SN - 1021-9986 AU - Ghanadzadeh, Hossein AU - Daghbandan, Allahyar AU - Akbarizadeh, Mohammd AD - Department of Chemical Engineering, Faculty of Engineering,Guilan University , P.O. Box 4163-3756 Rasht, I.R. IRAN AD - Department of Chemical Engineering, Faculty of Engineering,Guilan University , P.O. Box 4163-3756 Rasht, I.R. IRAN Y1 - 2014 PY - 2014 VL - 33 IS - 1 SP - 67 EP - 73 KW - Solid-liquid equilibrium KW - Isotactic poly (1-butene) KW - GMDH type-neural network KW - Organic solvents DO - 10.30492/ijcce.2014.7197 N2 - Isotactic poly (1-butene), ipbu-1, was synthesized by using a metallocene catalyst. The thermodynamic phase behavior of polymer–organic solvents systems is very important in every polymer application.  In this paper, the solid–liquid equilibrium of ipbu-1 with different organic solvents (1-heptyne, cyclo octane) was studied by a mathematical model. By considering the experiments temperature-mole fraction results, phase diagram of the polymer solvent systems could be constructed. The temperature and activity coefficient based on mole fraction phase diagrams were predicted by using Pareto genetic design of GMDH-type neural network. The results were very encouraging and congruent with the experimental data.   UR - https://ijcce.ac.ir/article_7197.html L1 - https://ijcce.ac.ir/article_7197_62a66b9e34c003a69c2eb5e8e49ac67b.pdf ER -