Correlation of Liquid-Liquid Equilibrium of Four Binary Hydrocarbon-Water Systems, Using an Improved Artificial Neural Network Model

Journal of the Korean Chemical Society

Yan Hong Shen¹  Hui Chao Lv¹ 

关键词: Hydrocarbon-water system;    Liquid-liquid equilibrium;    Artificial neural network;    Correlation;   

DOI  :  

学科分类：化学（综合）

来源: Korean Chemical Society

【 摘 要 】

A back propagation artificial neural network model with one hidden layer is established to correlate the liquidliquid equilibrium data of hydrocarbon-water systems. The model has four inputs and two outputs. The network is systematically trained with 48 data points in the range of 283.15 to 405.37K. Statistical analyses show that the optimised neural network model can yield excellent agreement with experimental data(the average absolute deviations equal to 0.037% and 0.0012% for the correlated mole fractions of hydrocarbon in two coexisting liquid phases respectively). The comparison in terms of average absolute deviation between the correlated mole fractions for each binary system and literature results indicates that the artificial neural network model gives far better results. This study also shows that artificial neural network model could be developed for the phase equilibria for a family of hydrocarbon-water binaries.

【 授权许可】

Unknown