Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

Spectrochimica Acta - Part B Atomic Spectroscopy

Volumn 70, Issue , 2012, Pages 24-32

  Anderson, Ryan B ^a   Bell III, James F ^b   Wiens, Roger C ^c   Morris, Richard V ^d   Clegg, Samuel M ^c  

^a Department of Obstetrics Gynecology   (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

^c LOS ALAMOS NATIONAL LABORATORY   (United States)

^d NASA JOHNSON SPACE CENTER   (United States)

Author keywords

ChemCam; Laser induced breakdown spectroscopy; Mars; Multivariate analysis

Indexed keywords

BAYESIAN INFORMATION CRITERION; CHEMCAM; CHEMICAL COMPOSITIONS; CLUSTERING METHODS; HIER-ARCHICAL CLUSTERING; K-MEANS CLUSTERING; K-MEANS CLUSTERING ALGORITHM; K-MEANS METHOD; MARS; MARS SCIENCE LABORATORY; MULTI VARIATE ANALYSIS; OPERATIONAL CONDITIONS; OPTIMAL NUMBER; PARTIAL LEAST SQUARE (PLS); PARTIAL LEAST-SQUARES REGRESSION; PRESSED POWDERS; PRIOR KNOWLEDGE; QUANTITATIVE CHEMICAL ANALYSIS; ROCK SLABS; ROOT MEAN SQUARED ERRORS; SAMPLE COMPOSITION; SI EMISSION; SOFT INDEPENDENT MODELING OF CLASS ANALOGIES; STAND-OFF DISTANCE (SOD); STATISTICAL SIGNIFICANCE; TEST SETS; TRAINING SAMPLE; TRAINING SET SELECTION; TRAINING SETS;

ATOMIC EMISSION SPECTROSCOPY; CARBON DIOXIDE; ITERATIVE METHODS; MARTIAN SURFACE ANALYSIS; SAMPLING;

LASER INDUCED BREAKDOWN SPECTROSCOPY;

EID: 84862198798     PISSN: 05848547     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sab.2012.04.004     Document Type: Article

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