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January 1, 2014Journal of Analytical Atomic Spectrometry

A novel approach for the quantitative analysis of multiple elements in steel based on laser-induced breakdown spectroscopy (LIBS) and random forest regression (RFR)

Tianlong Zhang Long Liang Kai Wang Hongsheng Tang Xiao‐Feng Yang Yixiang Duan Hua Li

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Abstract

LIBS combined with random forest regression (RFR) was proposed for the quantitative analysis of multiple elements in fourteen steel samples.

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Cite This Study

Zhang et al. (2014) studied this question.

synapsesocial.com/papers/69d88a7b18b0ca7f91d180fc https://doi.org/10.1039/c4ja00217b

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Laser-Induced Breakdown Spectroscopy—Capabilities and LimitationsOriginal Research · 2009 · 230 citations
2Laser-Induced Breakdown Spectroscopy (LIBS), Part II: Review of Instrumental and Methodological Approaches to Material Analysis and Applications to Different FieldsReview · 2012 · 1,500 citations
3Spatially Resolved, Laser-Induced Breakdown Spectroscopy, Development, and Application for the Analysis of Al and Si in Nickel-Based AlloysOriginal Research · 2006 · 29 citations
4Comparison of principal components regression, partial least squares regression, multi-block partial least squares regression, and serial partial least squares regression algorithms for the analysis of Fe in iron ore using LIBSOriginal Research · 2011 · 102 citations
5Liquid steel analysis with laser-induced breakdown spectrometry in the vacuum ultravioletOriginal Research · 2003 · 134 citations

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