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https://doi.org/10.2139/ssrn.4637592

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inferredcites →https://doi.org/10.1016/b978-0-12-409547-2.14878-4openalex-extracted
Pre-processing Methods
inferredcites →https://doi.org/10.1016/j.fuel.2008.06.016openalex-extracted
Using principal component analysis to find the best calibration settings for simultaneous spectroscopic determination of several gasoline properties
inferredcites →https://doi.org/10.1016/j.fuel.2012.04.027openalex-extracted
Fast-HRGC method for quantitative determination of benzene in gasoline
inferredcites →https://doi.org/10.1016/j.fuel.2013.07.110openalex-extracted
Classification of gasoline as with or without dispersant and detergent additives using infrared spectroscopy and multivariate classification
inferredcites →https://doi.org/10.1016/j.fuel.2017.02.041openalex-extracted
Detection and estimation of Super premium 95 gasoline adulteration with Premium 91 gasoline using new NIR spectroscopy combined with multivariate methods
inferredcites →https://doi.org/10.1016/j.fuel.2019.116114openalex-extracted
Detection and classification of diesel-biodiesel blends by LDA, QDA and SVM approaches using an electronic nose
inferredcites →https://doi.org/10.1016/j.fuel.2020.118854openalex-extracted
Discrimination of oils and fuels using a portable NIR spectrometer
inferredcites →https://doi.org/10.1016/j.infrared.2022.104354openalex-extracted
Quality classification of gasoline samples based on their aliphatic to aromatic ratio and analysis of PONA content using genetic algorithm based multivariate techniques and ATR-FTIR spectroscopy
inferredcites →https://doi.org/10.1016/j.saa.2018.09.059openalex-extracted
Fourier transform infrared spectroscopy and chemometrics for the discrimination of paper relic types
inferredcites →https://doi.org/10.1016/j.talanta.2017.07.094openalex-extracted
Portable near infrared spectroscopy applied to fuel quality control
inferredcites →https://doi.org/10.1016/j.trac.2017.04.011openalex-extracted
Monitoring petroleum fuel adulteration: A review of analytical methods
inferredcites →https://doi.org/10.1021/ac9507294openalex-extracted
Analysis of Gasolines by FT-IR Spectroscopy
inferredcites →https://doi.org/10.1021/acs.energyfuels.6b01937openalex-extracted
Classification of Fuel Blends Using Exploratory Analysis with Combined Data from Infrared Spectroscopy and Stable Isotope Analysis
inferredcites →https://doi.org/10.1021/acs.energyfuels.8b02368openalex-extracted
Gasoline Quality Assessment Using Fast Gas Chromatography and Partial Least-Squares Regression for the Detection of Adulterated Gasoline
inferredcites →https://doi.org/10.1021/ef050031lopenalex-extracted
Identification of Adulteration of Gasoline Applying Multivariate Data Analysis Techniques HCA and KNN in Chromatographic Data
inferredcites →https://doi.org/10.1021/ef050203eopenalex-extracted
Determination of Gasoline Adulteration by Principal Components Analysis-Linear Discriminant Analysis Applied to FTIR Spectra
inferredcites →https://doi.org/10.1039/c3ay41907jopenalex-extracted
Principal component analysis
inferredcites →https://doi.org/10.1080/10739149.2018.1470535openalex-extracted
Quantification of anhydrous ethanol and detection of adulterants in commercial Brazilian gasoline by Raman spectroscopy
inferredcites →https://doi.org/10.1080/15567030701258444openalex-extracted
Determination of Ethanol in Blend Petrol by Gas Chromatography and Fourier Transform Infrared Spectroscopy
inferredcites →https://doi.org/10.1155/2021/5845422openalex-extracted
Comparison of Machine Learning Classification Methods for Determining the Geographical Origin of Raw Milk Using Vibrational Spectroscopy
inferredcites →https://doi.org/10.1365/s10337-003-0065-zopenalex-extracted
Automotive Gasoline Quality Analysis by Gas Chromatography: Study of Adulteration
inferredcites →https://doi.org/10.1366/12-06723openalex-extracted
Optimizing Savitzky–Golay Parameters for Improving Spectral Resolution and Quantification in Infrared Spectroscopy
inferredcites →https://doi.org/10.3390/lubricants11060268openalex-extracted
Classification of Lubricating Oil Types Using Mid-Infrared Spectroscopy Combined with Linear Discriminant Analysis–Support Vector Machine Algorithm
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