Accurate quantification of alkalinity of sintered ore by random forest model based on PCA and variable importance (PCA-VI-RF)-Reference-Cited by-同舟云学术

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Accurate quantification of alkalinity of sintered ore by random forest model based on PCA and variable importance (PCA-VI-RF)

Published:2020-02-25 Issue:7 Volume:59 Page:2042
ISSN:1559-128X
Container-title:Applied Optics
language:en
Short-container-title:Appl. Opt.

Author:

Deng Xinxin,Yang Guang,Zhang Hong,Chen Guanyu

Funder

National Natural Science Foundation of China

Jilin Provincial Environmental Protection Agency of China

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

Reference38 articles.

1. Classification of iron ore based on acidity and alkalinity by laser induced breakdown spectroscopy coupled with N-nearest neighbours (N3)

2. Analysis of sintered products of iron ore fines by flame atomic absorption spectrometry using a matrix modifier

3. Mineral changes and trace element releases during extraction of alumina from high aluminum fly ash in Inner Mongolia, China

4. In-situ DRIFTS investigation on the selective catalytic reduction of NO with NH3 over the sintered ore catalyst

5. Acid leaching and dissolution of major sulphide ore minerals: processes and galvanic effects in complex systems

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1. Rapid quantitative analysis of multiple rare earth elements in NdFeB alloys based on laser-induced breakdown spectroscopy (LIBS) and random forest (RF);Spectrochimica Acta Part B: Atomic Spectroscopy;2024-07

2. 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

3. Rapid Quantitative Analysis of Multiple Rare Earth Elements In Ndfeb Alloys Based on Laser-Induced Breakdown Spectroscopy (Libs) And Random Forest (Rf);2024

4. Quantitative Detection of Quartz Sandstone SiO2 Grade Using Polarized Infrared Absorption Spectroscopy with Convolutional Neural Network Model;Journal of Spectroscopy;2023-04-04

5. 基于LIBS在线分析烧结矿混合料成分及校正水分影响;Chinese Journal of Lasers;2023

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