کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1169818 | 960653 | 2008 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quantitative structure-property relationship study for estimation of quantitative calibration factors of some organic compounds in gas chromatography
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
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چکیده انگلیسی
Quantitative structure-property relationship (QSPR) models have been used to predict and explain gas chromatographic data of quantitative calibration factors (fM). This method allows for the prediction of quantitative calibration factors in a variety of organic compounds based on their structures alone. Stepwise multiple linear regression (MLR) and non-linear radial basis function neural network (RBFNN) were performed to build the models. The statistical characteristics provided by multiple linear model (R2Â =Â 0.927, RMSÂ =Â 0.073; AARDÂ =Â 6.34% for test set) indicated satisfactory stability and predictive ability, while the predictive ability of RBFNN model is somewhat superior (R2Â =Â 0.959; RMSÂ =Â 0.0648; AARDÂ =Â 4.85% for test set). This QSPR approach can contribute to a better understanding of structural factors of the compounds responsible for quantitative analysis by gas chromatography, and can be useful in predicting the quantitative calibration factors of other compounds.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytica Chimica Acta - Volume 612, Issue 2, 7 April 2008, Pages 126-135
Journal: Analytica Chimica Acta - Volume 612, Issue 2, 7 April 2008, Pages 126-135
نویسندگان
Feng Luan, Hui Tao Liu, Yingying Wen, Xiaoyun Zhang,