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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
aygxy_lhc: 金币+10, ★★★★★最佳答案, 谢谢了! 2021-04-29 17:03:32
sunshan4379: LS-EPI+1, 感谢应助! 2021-05-01 10:47:00
Designing and optimizing a parallel neural networkmodel for predicting the solubility of diosgenin in n-alkanols
作者:Lv, HC (Lv, Huichao)[ 1 ] ; Tian, DY (Tian, Dayong)[ 1 ]
CHINESE JOURNAL OF CHEMICAL ENGINEERING
卷: 29 期: 1 页: 288-294
DOI: 10.1016/j.cjche.2020.09.009
出版年: JAN 2021
文献类型:Article
摘要
Accurate estimation of the solubility of a chemical compound is an important issue formany industrial processes. To 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) model. The 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 precision. Moreover, 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. (C) 2020 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights reserved.
关键词
作者关键词:Solubility; Diosgenin; Parallel neural network model; NRTL model
作者信息
通讯作者地址:
Anyang Inst Technol, Sch Chem & Environm Engn, Anyang 455000, Peoples R China.
通讯作者地址: Lv, HC (通讯作者)
Anyang Inst Technol, Sch Chem & Environm Engn, Anyang 455000, Peoples R China.
地址:
[ 1 ] Anyang Inst Technol, Sch Chem & Environm Engn, Anyang 455000, Peoples R China
电子邮件地址:20160471@ayit.edu.cn
基金资助致谢
基金资助机构 授权号
Science and Technology Plan Project of Henan Province
192102310232
查看基金资助信息
出版商
CHEMICAL INDUSTRY PRESS CO LTD, NO 13, QINGNIANHU SOUTH ST, DONGCHENG DIST, BEIJING 100011, PEOPLES R CHINA
类别 / 分类
研究方向:Engineering
Web of Science 类别:Engineering, Chemical
文献信息
语言:English
入藏号: WOS:000636564100033
ISSN: 1004-9541
eISSN: 2210-321X
其他信息
IDS 号: RH9XB
Web of Science 核心合集中的 "引用的参考文献": 29
Web of Science 核心合集中的 "被引频次": 0
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