摘要
基于[C4mim]Br/K3C6H5O7离子液体双水相体系相平衡的特征,提出了"子网络"的概念和"实验数据放大适当倍数"的策略,将体系在278.15 K、298.15 K和318.15 K温度下的相平衡数据分为训练和检验样本,建立了相应的神经网络数据模型.模型对实验测量的依赖性较低,且计算精度优于文献中的Setschenowtype方程,有助于更好地了解该体系的相行为.
The concept of subnetwork and the strategy to magnify experiment data with an appropriate multiple were proposed based on the characteristic of the phase equilibrium data of the aqueous two-phase system formed by[C4mim]Br / K3C6H5O7. Then the neural network model was established by dividing the collected data at 278. 15 K,298. 15 K and 318. 15 K into training and validation samples. The suggested model was slightly dependent on experiment and outperformed the Setschenow-type equation in terms of calculation accuracy.
出处
《信阳师范学院学报（自然科学版）》
CAS
北大核心
2015年第3期403-405,共3页
Journal of Xinyang Normal University(Natural Science Edition)
基金
国家自然科学基金项目(21406002)
关键词
离子液体
双水相体系
相平衡
子网络
ionic liquid
aqueous two-phase system
phase equilibrium
subnetwork
