Enhanced discrimination and calibration of biomass NIR spectral data using non-linear kernel methods

Bioresource Technology

Volumn 99, Issue 17, 2008, Pages 8445-8452

  Labbé, Nicole ^a   Lee, Seung Hwan ^b   Cho, Hyun Woo ^c   Jeong, Myong K ^c   André, Nicolas ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

^b NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^c University of Tennessee Knoxville   (United States)

Author keywords

Ash content; Biomass; Kernel PCA; Kernel PLS; Near infrared

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; BIOLOGICAL MATERIALS; BIOMASS; COAL; CURVE FITTING; DECISION MAKING; FINANCIAL DATA PROCESSING; INFRARED DEVICES; INFRARED SPECTROSCOPY; LEAST SQUARES APPROXIMATIONS; MULTIVARIANT ANALYSIS; NEAR INFRARED SPECTROSCOPY; RANDOM VARIABLES; REGRESSION ANALYSIS; RENEWABLE ENERGY RESOURCES; SPECTROSCOPIC ANALYSIS; SPECTRUM ANALYSIS;

COEFFICIENT OF CORRELATION; IN ORDER; KERNEL PCA; KERNEL PLS; MULTIVARIATE ANALYSIS (MVA); NEAR INFRA-RED (NIR); NON-LINEAR; ORTHOGONAL SIGNAL CORRECTION (OSC); PARTIAL LEAST SQUARES (PLS 1); PRINCIPAL COMPONENT ANALYSIS (PCA); RAPID METHODS; SPECTRAL DATA; STATISTICAL APPROACHES;

PRINCIPAL COMPONENT ANALYSIS;

CHARCOAL;

ASH; BIOMASS; CALIBRATION; NONLINEARITY;

ARTICLE; ASH; BIOMASS; CALIBRATION; CLASSIFICATION; CORRELATION COEFFICIENT; KERNEL METHOD; MULTIVARIATE ANALYSIS; NEAR INFRARED SPECTROSCOPY; NONLINEAR SYSTEM; ORTHOGONAL ROTATION; PARTIAL LEAST SQUARES REGRESSION; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

BIOMASS; CALIBRATION; LEAST-SQUARES ANALYSIS; MODELS, STATISTICAL; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; SPECTROSCOPY, NEAR-INFRARED; WOOD;

EID: 47749110578     PISSN: 09608524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biortech.2008.02.052     Document Type: Article

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