CATEGORY: DIESEL
Talanta, Available online 20 November 2012, In
Press, Accepted Manuscript
Feature
selection strategies for quality screening of diesel samples by infrared
spectrometry and linear discriminant analysis
Mohammadreza Khanmohammadi a, Amir Bagheri Garmarudi a, b, Miguel de
la Guardia c
a Chemistry Department, Faculty of Science, IKIU, Qazvin, Iran
b Department of Chemistry & Polymer Laboratories, Engineering Research
Institute, Tehran, Iran
c Department of Analytical Chemistry, University of Valencia, 50 Dr. Moliner
Street, E-46100 Burjassot, Valencia, Spain
Abstract
Describes
a rapid approach developed for the characterization of diesel quality, based on
attenuated total reflectance – Fourier transform infrared (ATR-FTIR)
spectrometry. The method could be useful
for diagnosing sample quality condition.
Linear discriminant analysis (LDA) was employed as a supervised
technique to process the spectrometric data. The role of variable selection
methods was also evaluated. Researchers
applied successive projection algorithm (SPA) and genetic algorithm (GA)
feature selection techniques prior to the discriminative procedure. Its purpose was to compare the effect of
feature selection procedures on classification capability of IR spectrometry
for the diesel samples according to their quality passed or quality failed
situation. Authors propose SPA-LDA
together with ATR-FTIR spectrometry as a fast screening analytical test for the
evaluation of quality passed/failed situation in diesel samples.
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