Designing and optimizing a parallel neural network model for predicting the solubility of diosgenin in n-alkanols

作     者：Huichao Lv Dayong Tian Huichao Lv;Dayong Tian

作者机构：School of Chemical&Environmental EngineeringAnyang Institute of TechnologyAnyang 455000China 

基　　金：supported by the Science and Technology Plan Project of Henan Province (No. 192102310232) 

出 版 物：《Chinese Journal of Chemical Engineering》 (中国化学工程学报（英文版）)

年 卷 期：2021年第34卷第1期

页      码：288-294页

摘      要：Accurate estimation of the solubility of a chemical compound is an important issue for many industrial proce *** overcome the defects of some thermodynamic models and simple correlations,a parallel neural network(PNN) model was conceived and optimized to predict the solubility of diosgenin in seven n-alkanols(C_(1)-C_(7)).The linear regression analysis of the parity plots indicates that the PNN model can give more accurate descriptions of the solubility of diosgenin than the ordinary neural network(ONN) *** comparison of the average root mean square deviation(RMSD) shows that the suggested model has a slight advantage over the thermodynamic NRTL model in terms of the calculating ***,the PNN model can reflect the effects of the temperature and the chain length of the alcohol solvent on the solution behavior of diosgenin correctly and can estimate its solubility in the n-alkanols with more carbon atoms.

主 题 词：Solubility Diosgenin Parallel neural network model NRTL model 

学科分类：081704[081704] 07[理学] 070304[070304] 08[工学] 0817[工学-轻工类] 0703[理学-化学类] 

核心收录：

D　O　I：10.1016/j.cjche.2020.09.009

馆 藏 号：203102105...