دانلود مقاله ISI انگلیسی شماره 89464
ترجمه فارسی عنوان مقاله

رویکرد انتخاب فاصله زمانی معکوس برای تعریف نمونه های دیزلی / بیودیزل

عنوان انگلیسی
A non-equidistant wavenumber interval selection approach for classifying diesel/biodiesel samples
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
89464 2017 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Chemometrics and Intelligent Laboratory Systems, Volume 167, 15 August 2017, Pages 171-178

پیش نمایش مقاله
پیش نمایش مقاله  رویکرد انتخاب فاصله زمانی معکوس برای تعریف نمونه های دیزلی / بیودیزل

چکیده انگلیسی

In recent years, spectroscopy techniques such as Near infrared (NIR) and Fourier Transform Infrared (FTIR) have been widely adopted as analytical tools in different fields and with several purposes. NIR and FTIR data are typically comprised of hundreds or even thousands of highly correlated wavenumbers, fact that can jeopardize the accuracy of several statistical techniques. In light of that, wavenumber selection emerges as an important step in prediction and classification tasks based on spectroscopy data. This paper proposes a novel framework for wavenumber selection aimed at classifying samples into proper categories, which is applied to two data sets from the petroleum sector. The method relies on two main stages: determination of intervals based on the distance between the average spectra of the classes and selection of the most suitable intervals through cross-validation. An improvement in the misclassification rate was achieved for a NIR spectra data set of diesel, decreasing that metric from 13.90% to 11.63% after the application of the proposed method while retaining 23.19% of the original wavenumbers. As for the biodiesel FTIR data set, the method yielded a misclassification rate of 1.21% while retaining 4.95% of the original variables; misclassification rate was 4.71% when all wavenumbers were used. The proposed method also outperformed traditional approaches for wavenumber selection.