Abstract
A GMDH-type neural network was used to calculate liquid phase equilibrium data for the (water + ethanol or acetic acid + 2-ethyl-1-hexanol) ternary systems in the temperature range of 298.2–313.2 K. Using this method, a new model was proposed that is suitable for predicting the liquid–liquid equilibrium data. The proposed model was “trained” before the requested calculation. The data set was divided into two parts: 70% were used as data for “training” and 30% were used as a test set, which were randomly extracted from the database. After the training on the input–output process, the predicted values were compared with experimental values to evaluate the performance of the group method of data handling neural network method.
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