Nondestructive speciation of solid mixtures by multivariate calibration of X-ray absorption near-edge structure using artificial neural networks and partial least-squares

Analytical Sciences

Volumn 16, Issue 6, 2000, Pages 597-602

  Kuno, Akihito ^a   Matsuo, Motoyuki ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ABSORPTION SPECTRA; CHEMICAL SPECIATION; FLUORESCENCE; IRON COMPOUNDS; LEAST SQUARES APPROXIMATIONS; LIGHT ABSORPTION; MIXTURES; MULTIVARIABLE SYSTEMS; SUPERCONDUCTING MATERIALS; X RAY ABSORPTION; X RAY ABSORPTION NEAR EDGE STRUCTURE SPECTROSCOPY;

MULTIVARIATE CALIBRATION; MULTIVARIATE CALIBRATION METHODS; PARTIAL LEAST SQUARE (PLS); PREDICTION PERFORMANCE; QUANTITATIVE DETERMINATIONS; SELF-ABSORPTION EFFECTS; SPECTRAL DISTORTIONS; X-RAY ABSORPTION NEAR-EDGE STRUCTURE;

NEURAL NETWORKS;

IRON;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CALIBRATION; CHEMICAL ANALYSIS; CHEMICAL STRUCTURE; SOLID; X RAY ANALYSIS;

EID: 0033922704     PISSN: 09106340     EISSN: None     Source Type: Journal    
DOI: 10.2116/analsci.16.597     Document Type: Article

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