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Volumn 27, Issue 12, 2007, Pages 2460-2463
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Application of PCA-SVR to NIR prediction model for tobacco chemical composition
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Author keywords
Chemometrics; Near infrared spectroscopy; Support vector regression; Tobacco
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Indexed keywords
AGRICULTURAL PRODUCTS;
ARTIFICIAL INTELLIGENCE;
BACKPROPAGATION;
C (PROGRAMMING LANGUAGE);
COMPUTER NETWORKS;
CURVE FITTING;
FOOD PROCESSING;
FRUITS;
INFRARED DEVICES;
KETONES;
LEAST SQUARES APPROXIMATIONS;
LINEAR REGRESSION;
MATHEMATICAL MODELS;
METROPOLITAN AREA NETWORKS;
NETWORK PROTOCOLS;
NITROGEN;
PRINCIPAL COMPONENT ANALYSIS;
REGRESSION ANALYSIS;
SPECTROSCOPIC ANALYSIS;
SPECTRUM ANALYSIS;
SUGAR (SUCROSE);
SUGARS;
TOBACCO;
ARTIFICIAL NEURONS;
BACK PROPAGATION (BP);
CALIBRATION MODELS;
CHEMICAL COMPOSITIONS;
CROSS-VALIDATION (CV);
KERNEL FUNCTIONS;
LEAVE-ONE-OUT (LOO);
LOSS FUNCTIONS;
NEAR INFRA-RED (NIR);
NEAR INFRARED DIFFUSE REFLECTANCE;
OPTIMAL MODELING;
PARTIAL LEAST SQUARE (PLS);
PENALTY COEFFICIENT;
PREDICTION MODELING;
REDUCTIVE SUGAR;
REGRESSION (R2);
ROOT-MEAN-SQUARE-ERRORS (RMSE);
SUPPORT VECTOR REGRESSION (SVR);
SVM MODEL;
TOBACCO SAMPLES;
TOTAL NITROGEN (TN);
INFRARED SPECTROSCOPY;
PLANT EXTRACT;
ARTICLE;
CHEMISTRY;
EVALUATION;
MATHEMATICAL COMPUTING;
METHODOLOGY;
NEAR INFRARED SPECTROSCOPY;
PLANT LEAF;
PRINCIPAL COMPONENT ANALYSIS;
TOBACCO;
MATHEMATICAL COMPUTING;
PLANT EXTRACTS;
PLANT LEAVES;
PRINCIPAL COMPONENT ANALYSIS;
SPECTROSCOPY, NEAR-INFRARED;
TOBACCO;
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EID: 38049138720
PISSN: 10000593
EISSN: None
Source Type: Journal
DOI: None Document Type: Article |
Times cited : (28)
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References (16)
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