Correction: Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model

Correction: Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model

Correction for 'Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model' by Y. M. Guo et al. , J. Anal. At. Spectrom. , 2018, 33 , 1330-1335, DOI: 10.1039/C8JA00119G.

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Veröffentlicht in:Journal of analytical atomic spectrometry 2020-07, Vol.35 (7), p.1487-1487
Hauptverfasser: Guo, Y. M, Guo, L. B, Hao, Z. Q, Tang, Y, Ma, S. X, Zeng, Q. D, Tang, S. S, Li, X. Y, Lu, Y. F, Zeng, X. Y
Format: Artikel
Sprache:eng
Schlagworte:
Iron compounds
Iron ores
Laser induced breakdown spectroscopy
Least squares
Model accuracy
Spectroscopic analysis
Spectrum analysis
Support vector machines
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Zusammenfassung:Correction for 'Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model' by Y. M. Guo et al. , J. Anal. At. Spectrom. , 2018, 33 , 1330-1335, DOI: 10.1039/C8JA00119G.
ISSN:0267-9477
1364-5544
DOI:10.1039/d0ja90040k