6533b831fe1ef96bd129835a

RESEARCH PRODUCT

Quality based classification of gasoline samples by ATR-FTIR spectrometry using spectral feature selection with quadratic discriminant analysis

Miguel De La GuardiaAmir Bagheri GarmarudiKeyvan GhasemiMohammadreza Khanmohammadi

subject

business.industryGeneral Chemical EngineeringOrganic ChemistryAnalytical chemistryEnergy Engineering and Power TechnologyPattern recognitionFeature selectionQuadratic classifierMass spectrometryFuel TechnologyDiscriminative modelFeature (computer vision)Genetic algorithmArtificial intelligenceGasolinebusinessDykstra's projection algorithmMathematics

description

Abstract A chemometric approach has been developed for characterization of gasoline samples regarding their quality. Attenuated total reflectance – infrared spectrometric data were processed by genetic algorithm (GA) and successive projection algorithm (SPA) feature selection techniques, being employed as an initial step prior to apply a discriminative tool. It was aimed to classify the fuel samples according to their quality passed/failed data. Chemometric predictive procedures were developed using quadratic discriminant analysis (QDA) combined with GA and SPA as a feature subset and feature selection strategy. Results showed 93.3% and 95.6% accuracy for SPA-QDA and GA-QDA models respectively.

yearjournalcountryeditionlanguage
2013-09-01Fuel
https://doi.org/10.1016/j.fuel.2013.04.001