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The Support Vector Classification (SVC) model was constructed in this study by applying the near infrared (NIR) analysis technology combined with the chemometrics method to classify and distinguish 11 types of vegetable oil, including "restaurant waste oil". Partial least squares-discriminate analysis (PLS-DA) and GA-SVC classification models were(More)
The qualitative model for rapidly discriminating the waste oil and four normal edible vegetable oils is developed using near infrared spectroscopy combined with support vector machine (SVM). Principal component analysis (PCA) has been carried out on the base of the combination of spectral pretreatment of vector normalization, first derivation and nine point(More)
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