Abstract

The potential use of artificial neural networks to describe liquid–liquid phase equilibria in ternary systems under polythermal conditions is considered. The study was carried out on the example of ten ternary systems, including binary splitting subsystems of water–esters of carboxylic acids, which determines the phase splitting in ternary systems (the third component is alcohol or carboxylic acid). The features of the selected network architecture are presented, and the results, with a critical assessment of the accuracy of the calculations, are given in the tables. Approximations based on artificial neural networks are compared with calculations based on the non-random two-liquid (NRTL) model.

中文翻译：

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人工神经网络在三组分系统液-液平衡数据分析中的应用

摘要

考虑了人工神经网络在多热条件下描述三元系统中液-液相平衡的潜在用途。该研究以十个三元体系为例进行了研究，包括水-羧酸酯的二元分裂子系统，它决定了三元体系中的相分裂（第三组分是醇或羧酸）。介绍了所选网络架构的特征，并在表格中给出了结果，并对计算的准确性进行了严格评估。将基于人工神经网络的近似值与基于非随机二液 (NRTL) 模型的计算进行比较。