Citation: Nasser Goudarzi, M. Arab Chamjangali, A. H. Amin. Calculation of Hildebrand Solubility Parameters of Some Polymers Using QSPR Methods Based on LS-SVM Technique and Theoretical Molecular Descriptors[J]. Chinese Journal of Polymer Science, ;2014, 32(5): 587-594. doi: 10.1007/s10118-014-1423-z shu

Calculation of Hildebrand Solubility Parameters of Some Polymers Using QSPR Methods Based on LS-SVM Technique and Theoretical Molecular Descriptors

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Faculty of Chemistry, Shahrood University of Technology, Box 316, Shahrood, Iran

Corresponding author: Nasser Goudarzi,
Received Date: 15 July 2013
Revised Date: 24 November 2013

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.
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沈阳化工大学材料科学与工程学院沈阳 110142