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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
aygxy_lhc: 金币+10, ★★★很有帮助, 谢谢了! 2020-06-29 20:29:35
心静_依然: LS-EPI+1, 感谢应助 2020-07-09 08:42:14
Circuit-based neural network models for estimating the solubility of diosgenin
作者:Lv, HC (Lv, Huichao)[ 1 ] ; Liu, NN (Liu, Nana)[ 1 ] ; Tian, DY (Tian, Dayong)[ 1 ] ; Zeng, YW (Zeng, Yuwen)[ 1 ] ; Li, BL (Li, Baoli)[ 1 ]
CHEMICAL ENGINEERING COMMUNICATIONS
DOI: 10.1080/00986445.2019.1663181
Early access icon在线发表日期: SEP 2019
文献类型:Article; Early Access
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摘要
Several new circuit-based neural network models were conceived and utilized to estimate the solubility of diosgenin. Six mixed alcohol solvents and a pure solvent (carbon tetrachloride) were selected as the model systems to demonstrate the point of interest. To make full use of the collected solubility data of diosgenin in these solvents, they were categorized into training, testing and validation sets and a 5-fold cross validation was adopted in the buildup of the model. The results of the statistical analysis and the sum of ranking differences method indicate the parallel-serial neural network model gives more accurate description of the solubility data of diosgenin in contrast to other patterns. It also outperforms two empirical equations in terms of calculating accuracy. In addition, this suggested model can exhibit the effect of the changes of the components and their proportions in solvent on the solution behavior of diosgenin correctly.
关键词
作者关键词:Circuit-based neural network; Diosgenin; Solubility; Mixed alcohol solvent; Carbon tetrachloride; Sum of ranking differences
KeyWords Plus:HIGH-PRESSURE; PREDICTION; OPTIMIZATION; ADSORPTION; DENSITY; SYSTEM; WATER; DYES
作者信息
通讯作者地址: Lv, HC (corresponding author)
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:prolvhuichao@126.com
基金资助致谢
基金资助机构显示详情 授权号
National Natural Science Foundation of China
U1404217
Key Science and Technology Project of Henan Province
172102310166
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出版商
TAYLOR & FRANCIS INC, 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA
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:000486174500001
ISSN: 0098-6445
eISSN: 1563-5201
其他信息
IDS 号: IY1TL
Web of Science 核心合集中的 "引用的参考文献": 30
Web of Science 核心合集中的 "被引频次": 0 |
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