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Citation: ZHOU Peng, MEI Hu, TIAN Fei-Fei, LI Zhi-Liang. Application of Support Vector Machine to Prediction of Refractive Index for High Molecular Weight Polymers[J]. Chinese Journal of Applied Chemistry, ;2006, 23(12): 1410-1412. shu

Application of Support Vector Machine to Prediction of Refractive Index for High Molecular Weight Polymers

ZHOU Peng ^a,b ,
MEI Hu ^c ,
TIAN Fei-Fei ^a ,
LI Zhi-Liang ^a,b,c,,

1.
a College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044;
2.
b State Key Laboratory of Chemo/Biosensing and Chemometrics, Changsha 410012;
3.
c Key Laboratory of Biomedical Engineering of Educational Ministry, Chongqing 400044

Corresponding author: LI Zhi-Liang,
Received Date: 25 December 2005
Available Online: 5 September 2006
Fund Project: 化学生物传感与计量学国家重点实验室基金(05-12-1) (05-12-1)重庆应用基础研究基金(01-3-6) (01-3-6)重庆大学创新基金(06-1-10)资助项目 (06-1-10)

Support vector machine(SVM) was employed in quantitative structure-property relationship(QSPR) study for analyzing the refractive indices(n) of 95 high molecular weight polymers.Comparisons was systematically made based on the results obtained with different methods of multiple linear regression(MLR),artificial neural network(ANN) and ones reported in literatures.It is suggested that SVM possesses both high modeling stability and good generalization ability,especially when applied to investigating both nonlinear systems and small samplings,yielding superior modeling results.The cumulative multiple correlation coefficient r²,cumulative cross-validated q² and external q_ext² are 0.943,0.938 and 0.919, respectively.Therefore it is believed that SVM has broad prospects and wide applications for the evaluation of polymer properties.
- support vector machine,
- quantitative structure-property relationship,
- high molecular weight polymer,
- refractive index
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