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year 28, Issue 2 (ICOP & ICPET 2022 2022)
ICOP & ICPET _ INPC _ ICOFS 2022, 28(2): 784-787 |
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Rezaei F, Rezaei M, Karimi P. Study of the effect of combination of principle component analysis with statistical method of support vector regression in laser induced breakdown spectroscopy. ICOP & ICPET _ INPC _ ICOFS 2022; 28 (2) :784-787
URL: http://opsi.ir/article-1-2657-en.html
URL: http://opsi.ir/article-1-2657-en.html
1- Department of Physics, K. N. Toosi University of Technology
2- Groups of Industrial Engineering, University of Science and Technology of Mazandaran
3- Department of Physics, South Tehran Branch, Islamic Azad University
2- Groups of Industrial Engineering, University of Science and Technology of Mazandaran
3- Department of Physics, South Tehran Branch, Islamic Azad University
Abstract: (515 Views)
In this paper, concentration of constituent elements of seven standard aluminum’S alloys is predicted by using statistical methods of support vector regression model (SVR and KSVR) and the combinational method of principal component analysis with support vector regression model (PCA_SVR and PCA-KSVR) in laser induced breakdown laser spectroscopy technique. The results of the analyzes showed that the PCA_KSVR method reported the most accurate concentration with the least error for Fe element.
Keywords: Laser induced breakdown spectroscopy, Concentration prediction, Principle component analysis, support vector regression.
Type of Study: Experimental |
Subject:
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