Partial Least Squares and Neural Networks for Quantitative Calibration of Laser-Induced Breakdown Spectroscopy (LIBS) of Geologic Samples

Details Partial Least Squares and Neural Networks for Quantitative Calibration of Laser-Induced Breakdown Spectroscopy (LIBS) of Geologic Samples Partial Least Squares and Neural Networks for Quantitative Calibration of Laser-Induced Breakdown Spectroscopy (LIBS) of Geologic Samples

Mar 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010lpi....41.2013a&link_type=abstract

41st Lunar and Planetary Science Conference, held March 1-5, 2010 in The Woodlands, Texas. LPI Contribution No. 1533, p.2013

Mathematics

Logic

Scientific paper

We have collected LIBS spectra of a diverse suite of well-characterized
geologic samples and compare the performance of partial least squares
regression and artificial neural networks in predicting quantitative
sample compositions.

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