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Prediction of viscosity for hydrocarbons by molecular shape indices and electrotopological state indices


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Prediction of viscosity for hydrocarbons by molecular shape indices and electrotopological state indices
Shi JingjieChen LipingChen WanghuaYang Hui
School of Chemical Engineering,NUST,Nanjing 210094,China
molecular shape indices electrotopological state indices hydrocarbons viscosity multiple linear regression quantitative structure-property relationship support vector method prediction
O621.21; X937
The quantitative relationship between viscosities and molecular structures of hydrocarbons is investigated based on the quantitative structure-property relationship(QSPR)principle.The model is constructed by using multiple linear regression(MLR)and support vector method(SVM)on a dataset that consists of 65 compounds.The dataset is randomly divided into a training set(52)and a testing set(13).Molecular descriptors are considered as inputs to the model,involving two kinds of descriptors(two Kappa molecular shape indices and nine electropological state indices).Results show that in terms of model fitting ability and prediction ability,the SVM model is obviously superior to the MLR model.In order to test the stability and prediction capability of the SVM model,good results are observed in Jackknifed cross validation.This paper provides a new and effective method for predicting viscosities of hydrocarbons.


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Last Update: 2014-08-31