A random-forest-assisted artificial-neural-network method for analysis of steel using laser-induced breakdown spectroscopy-Reference-Cited by-同舟云学术

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A random-forest-assisted artificial-neural-network method for analysis of steel using laser-induced breakdown spectroscopy

Published:2022-01 Issue: Volume:249 Page:168214
ISSN:0030-4026
Container-title:Optik
language:en
Short-container-title:Optik

Author:

Song Xiaoyan,Li Kuohu,Dai Kejie,Wang Xueqing,Du Haojie,Zhao Huanli

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference42 articles.

1. Optical microemission stimulated by a ruby laser;Brech;Appl. Spectrosc.,1962

2. Laser-Induced breakdown spectroscopy: fundamentals and applications;Noll,2012

3. Laser-induced breakdown spectroscopy;Singh,2007

4. Laser-induced breakdown spectroscopy (LIBS) fundamentals and applications;Miziolek,2006

5. Application of laser-induced breakdown spectroscopy (LIBS) in environmental monitoring;Zhang;Spectrochim. Acta, Part B,2021

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1. Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy;Plasma Science and Technology;2024-07-01

2. Accuracy Improvement of Mn Element in Aluminum Alloy by the Combination of LASSO-LSSVM and Laser-Induced Breakdown Spectroscopy;SPECTROSC SPECT ANAL;2024

3. Effects of feature engineering on the robustness of laser-induced breakdown spectroscopy for industrial steel classification;Spectrochimica Acta Part B: Atomic Spectroscopy;2024-02

4. Identification of fluoroquinolone-resistant Mycobacterium tuberculosis through high-level data fusion of Raman and laser-induced breakdown spectroscopy;Analytical Methods;2024

5. Microstructure classification of steel samples with different heat-treatment processes based on laser-induced breakdown spectroscopy (LIBS);Journal of Analytical Atomic Spectrometry;2024

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