正庚烷-甲苯-环丁砜液液平衡体系的神经网络模型

建立了正庚烷-甲苯-环丁砜液液平衡体系的神经网络模型.首先以303.15 K和313.15 K下的数据作为样本来训练神经网络,获得了优化的模型参数,而后用323.15 K下的数据来检验其预测能力.结果表明:在所研究的温度范围内,对相平衡数据能够给出较好的描述,3个温度下的平均绝对偏差分别为0.87%、0.71%和1.59%.

Neural Network Model of Liquid-Liquid Equilibrium of n-Heptane,Toluene and Sulfolane System

A back propagation neural network model with one hidden layer was established to predict the liquidliquid equilibrium data of n-heptane + toluene +( sulfolane and N-methylpyrrolidone) system under atmospheric pressure. The equilibrium data of 303. 15 K and 313. 15 K were employed to train the network,and then the optimized model parameters were obtained. The equilibrium data of 323. 15 K were used to validate its predicting capability. The results showed that average absolute deviations of the correlated( training) mole fractions from experimental data( 303. 15 K and 313. 15 K) were 0.87% and 0. 71%,respectively,and that of the predicted mole fractions from experimental data( 323. 15K) was 1. 59%.