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Prediction of viscosity of imidazolium-based ionic liquids using MLR and SVM algorithms
Zhao, Yongsheng1,2; Zhang, Xiangping1; Deng, Liyuan3; Zhang, Suojiang1
2016-09-02
Source PublicationCOMPUTERS & CHEMICAL ENGINEERING
ISSN0098-1354
Volume92Issue:SEPPages:37-42
Abstract

In this work, two models, one integrating the fragment contribution-corresponding states (FC-CS) method with multiple linear regression (MLR) algorithm and another. With support vector machine (SVM) algorithm, are proposed to predict the viscosity of imidazolium-based ionic liquids (ILs). The FC-CS method is applied to calculate the pseudo-critical volume and compressibility factor (V-c and Z(c)) as well as the boiling point temperature (T-b) which are employed to predict the viscosity with the MLR and SVM algorithms. A large data set of 1079 experimental data points of 45 imidazolium-based ILs covering a wide range of pressure and temperature is applied to validate the two models. The average absolute relative deviation (AARD) of the entire data set of the MLR and SVM is 24.2% and 3.95%, respectively. The nonlinear model developed by the SVM algorithm is much better than the linear model built by the MLR, which indicates the SVM algorithm is more reliable in the prediction of the viscosity of imidazolium-based ILs. (C) 2016 Elsevier Ltd. All rights reserved.

KeywordIonic Liquids Viscosity Support Vector Machine (Svm) Multiple Linear Regression (Mlr) Fragment Contribution-corresponding States (Fc-cs) Method
SubtypeArticle
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.compchemeng.2016.04.035
Indexed BySCI
Language英语
WOS KeywordSUPPORT VECTOR MACHINE ; DESIGN ; MODELS ; QSPR ; CONDUCTIVITIES ; SOLVENTS ; CAPTURE ; FUTURE
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Chemical
Funding OrganizationNational Basic Research Program of China(2015CB251403) ; National Natural Science Fund for Distinguished Young Scholars(21425625) ; key program of Beijing Municipal Natural Science Foundation(2141003) ; National Natural Science Foundation of China(21376242)
WOS IDWOS:000380513500003
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/21429
Collection多相复杂系统国家重点实验室
Affiliation1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing Key Lab Ion Liquids Clean Proc, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Chem & Chem Engn, Beijing 100049, Peoples R China
3.Norwegian Univ Sci & Technol, Dept Chem Engn, NO-7491 Trondheim, Norway
Recommended Citation
GB/T 7714
Zhao, Yongsheng,Zhang, Xiangping,Deng, Liyuan,et al. Prediction of viscosity of imidazolium-based ionic liquids using MLR and SVM algorithms[J]. COMPUTERS & CHEMICAL ENGINEERING,2016,92(SEP):37-42.
APA Zhao, Yongsheng,Zhang, Xiangping,Deng, Liyuan,&Zhang, Suojiang.(2016).Prediction of viscosity of imidazolium-based ionic liquids using MLR and SVM algorithms.COMPUTERS & CHEMICAL ENGINEERING,92(SEP),37-42.
MLA Zhao, Yongsheng,et al."Prediction of viscosity of imidazolium-based ionic liquids using MLR and SVM algorithms".COMPUTERS & CHEMICAL ENGINEERING 92.SEP(2016):37-42.
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