Cavity-constrained LIBS combined with the gray wolf optimization algorithm for optimizing bidirectional long short-term memory (GWO-BiLSTM) networks for classification prediction of different brands of cigarettes-Reference-Cited by-同舟云学术

Cavity-constrained LIBS combined with the gray wolf optimization algorithm for optimizing bidirectional long short-term memory (GWO-BiLSTM) networks for classification prediction of different brands of cigarettes

Published:2024 Issue: Volume: Page:
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Chen Junjie¹²^ORCID,Hao Xiaojian¹²,Mo Biming¹²,Li Shuaijun¹²^ORCID,Ma Junjie¹²,Liang Xiaodong¹²,Wang Zheng¹²,Zhang Heng³

Affiliation:

1. Science and Technology on Electronic Test and Measurement Laboratory, North University of China, Taiyuan, Shanxi, China

2. State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, Shanxi, China

3. Jincheng Research Institute of Opto-mechatronics Industry, Jincheng, Shanxi, China

Abstract

For the first time, cavity confinement-enhanced laser-induced breakdown spectroscopy (LIBS) combined with chemometrics has been used to realize high-precision classification and identification of different brands of cigarettes.

Funder

Fund for Shanxi Key Subjects Construction

National Natural Science Foundation of China

Shanxi University

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/JA/D4JA00143E

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4. Rapid classification of soils from different mining areas by laser-induced breakdown spectroscopy (LIBS) coupled with a PCA-based convolutional neural network

5. Spectroscopic measurement of the two-dimensional flame temperature based on a perovskite single photodetector