Feature selection enhances classification accuracy of magnesium alloys in LIBS spectra
Modern Applied Optics|更新时间:2026-02-24
|
Feature selection enhances classification accuracy of magnesium alloys in LIBS spectra
“Magnesium alloys are widely used in aerospace and other fields, and LIBS technology has a promising prospect for detecting magnesium alloys. Experts proposed a rapid classification method for magnesium alloys based on feature selection. After comparing various feature selection and classification models, the mRMR BPNN combination achieved first day and second day data testing accuracies of 99.4% and 92.5%, respectively, with only 180 features, significantly better than other methods. This provides a reliable means for rapid online detection and quality control of magnesium aluminum alloys and promotes the application of LIBS technology in industrial fields.”
Optics and Precision EngineeringVol. 34, Issue 4, Pages: 548-558(2026)
Quantitative analysis of Mo in alloy structural steel using laser-induced fluorescence assisted laser-induced breakdown spectroscopy
Establishment and optimization of aerial multispectral field straw mulch quantity inversion model
Simulating primary visual cortex to improve robustness of CNN neural network structures
Dense pedestrian detection algorithm in multi-branch non-anchor frame network
Gaussian process-based parameter identification and model current predictive control strategy of PMSM
Related Author
LIAO Jiale
GUO Enxin
WANG Sheng
YANG Ze'en
TANG Yun
MO Kaifeng
CUI Shuran
LIU Mengqi
Related Institution
Hunan Province Key Laboratory of Intelligent Sensors and Advanced Sensor Materials, School of Physics and Electronics Science, Hunan University of Science and Technology
Jilin Agricultural Machinery Research Institute
Changchun Agricultural Machinery Research Institute
College of Engineering and Technology, Jilin Agricultural University
College of Information Technology(Institute of Intelligent Agriculture), Jilin Agricultural University