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请帮忙看一下论文是否被SCI检索了，谢谢！
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作者: Huichao Lv, Dayong Tian 文题: Designing and optimizing a parallel neural network model for predicting the solubility of diosgenin in n-alkanols 期刊名: Chinese Journal of Chemical Engineering 期刊年份: 2021 卷(期),起止页码: 29：288-294. |
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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 查看较少数据字段 |
2楼2021-04-29 14:54:22