Classification of steel samples by laser-induced breakdown spectroscopy and random forest-Reference-Cited by-同舟云学术

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Classification of steel samples by laser-induced breakdown spectroscopy and random forest

Published:2016-10 Issue: Volume:157 Page:196-201
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Zhang Tianlong,Xia Donghui,Tang Hongsheng,Yang Xiaofeng,Li Hua

Funder

National Major Scientific Instruments and Equipment Development Projects of China

National Natural Science Foundation of China

Research Fund for the Doctoral Program of Higher Education of China

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference27 articles.

1. Automatic classification of steels by processing energy-dispersive X-ray spectra with artificial neural networks;Magallanes;J. Chem. Inf. Sci.,1998

2. Fracture characteristics of AISI D2 tool steel at different tempering temperatures using acoustic emission and fuzzy C-means clustering;Mohamad;Arab. J. Sci. Eng.,2013

3. Application of multi-scale feature extraction to surface defect classification of hot-rolled steels;Xu;Int. J. Miner. Metall. Mater.,2013

4. Methodology of classification of internal damage the steels during creep service;Dobrzański;J. Achiev. Mater. Manuf. Eng.,2006

5. Chip form classification in carbon steel turning through cutting force measurement and principal component analysis;Segreto;Procedia CIRP,2012

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4. Trigger-free LIBS using kHz and a few mJ laser in combination with random forest regression for the quantitative analysis of steel elements;Journal of Analytical Atomic Spectrometry;2024

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