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گواهی نمایه سازی مقاله An improved structure models to explain retention behavior of atmospheric nanoparticles

عنوان مقاله: An improved structure models to explain retention behavior of atmospheric nanoparticles
شناسه (COI) مقاله: JR_ICC-2-1_006
منتشر شده در فصلنامه ارتباطات شیمی ایران در سال ۱۳۹۲
مشخصات نویسندگان مقاله:

Sharmin Esmaeilpoor - Department of Chemistry, Payame Noor University, P.O. BOX 19395-4697 , Tehran, Iran
Zahra Shirzadi - Department of chemistry, Islamic Azad University, Shahreza Branch, Isfahan, Iran
Hadi Noorizadeh - Department of Chemistry, Payame Noor University, P.O. BOX 19395-4697 , Tehran, Iran

خلاصه مقاله:
The quantitative structure-retention relationship (QSRR) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multivariate regressions [e.g. the partial least squares (PLS)] as well as the nonlinear regressions [e.g. the kernel PLS (KPLS) and Levenberg- Marquardt artificial neural network (L-M ANN)] were utilized to construct the linear and nonlinear QSRR models. The correlation coefficient cross validation (Q^2) and relative error for test set L-M ANN model are 0.939 and 4.89, respectively. The resulting data indicated that L-M ANN could be used as a powerful modeling tool for the QSPR studies.

کلمات کلیدی:
Atmospheric nanoparticles, QSRR, GA-KPLS, Levenberg -Marquardt artificial neural network.

صفحه اختصاصی مقاله و دریافت فایل کامل: http://www.civilica.com/Paper-JR_ICC-2-1-JR_ICC-2-1_006.html