NDLI: Calculation of Hildebrand solubility parameters of some polymers using QSPR methods based on LS-SVM technique and theoretical molecular descriptors

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Chinese Journal of Polymer Science : Volume 32, Issue 4, April 2014

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Calculation of Hildebrand solubility parameters of some polymers using QSPR methods based on LS-SVM technique and theoretical molecular descriptors

Content Provider	Springer Nature Link
Author	Goudarzi, Nasser Arab Chamjangali, M. Amin, A. H.
Copyright Year	2014
Abstract	In this work, some chemometrics methods are applied for the modeling and prediction of the Hildebrand solubility parameter of some polymers. A genetic algorithm (GA) method is designed for the selection of variables to construct two models using the multiple linear regression (MLR) and least square-support vector machine (LS-SVM) methods in order to predict the Hildebrand solubility parameter. The MLR method is used to build a linear relationship between the molecular descriptors and the Hildebrand solubility parameter for these compounds. Then the LS-SVM method is utilized to construct the non-linear quantitative structure-activity relationship (QSAR) models. The results obtained using the LS-SVM method are then compared with those obtained for the MLR method; it was revealed that the LS-SVM model was much better than the MLR one. The root-mean-square errors of the training set and the test set for the LS-SVM model were 0.2912 and 0.2427, and the correlation coefficients were 0.9662 and 0.9518, respectively. This paper provides a new and effective method for predicting the Hildebrand solubility parameter for some polymers, and also reveals that the LS-SVM method can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.
Starting Page	587
Ending Page	594
Page Count	8
File Format	PDF
ISSN	02567679
Journal	Chinese Journal of Polymer Science
Volume Number	32
Issue Number	5
e-ISSN	14396203
Language	English
Publisher	Chinese Chemical Society and Institute of Chemistry, CAS
Publisher Date	2014-03-29
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Hildebrand solubility parameter Least square-support vector machine (LS-SVM) Quantitative structureproperty relationship (QSPR) Multiple linear regression (MLR) Genetic algorithm (GA) Polymer Sciences Industrial Chemistry/Chemical Engineering Characterization and Evaluation of Materials Condensed Matter Physics
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Chemical Engineering Polymers and Plastics

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