Browsing by Author "Bekri, Sezin"
Now showing items 1-3 of 3
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Application of deep neural network (DNN) for experimental liquid-liquid equilibrium data of water + butyric acid + 5-methyl-2-hexanone ternary systems
Bekri, Sezin; Dilek, Özmen; Aykut, Türkmenoğlu; Atilla, Özmen (Elsevier B.V., 2021)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 + ... -
Correlation of Experimental Liquid-Liquid Equilibrium Data for Ternary Systems Using NRTL and GMDH-Type Neural Network
Bekri, Sezin; Özmen, Dilek; Özmen, Atilla (Amer Chemical Soc, 2017)In this work liquid liquid equilibrium (LLE) data for the ternary systems (water + propionic acid + solvent) were experimentally obtained at atmospheric pressure and 298.2 K. The ternary systems show type-1 behavior of ... -
Deep learning based combining rule for the estimation of vapor-liquid equilibrium
Bekri, Sezin; Ozmen, Dilek; Ozmen, Atilla (Springer Heidelberg, 2023)Vapor-liquid equilibrium (VLE) data plays a vital role in the design, modeling and control of process equipment. In this study, to estimate the VLE data of binary systems, a deep neural network (DNN)-based combining rule ...