Rapid classification of archaeological ceramics via laser-induced breakdown spectroscopy coupled with random forest

2018 ◽  
Vol 149 ◽  
pp. 288-293 ◽  
Author(s):  
Juan Qi ◽  
Tianlong Zhang ◽  
Hongsheng Tang ◽  
Hua Li
2020 ◽  
Vol 35 (3) ◽  
pp. 518-525 ◽  
Author(s):  
Fangqi Ruan ◽  
Lin Hou ◽  
Tianlong Zhang ◽  
Hua Li

A modified backward elimination approach was proposed for feature selection (FS) to eliminate the redundant and irrelevant features from laser-induced breakdown spectroscopy (LIBS) spectra for the rapid classification of Chinese archaeological ceramics.


2015 ◽  
Vol 30 (2) ◽  
pp. 453-458 ◽  
Author(s):  
Liwen Sheng ◽  
Tianlong Zhang ◽  
Guanghui Niu ◽  
Kang Wang ◽  
Hongsheng Tang ◽  
...  

Laser-induced breakdown spectroscopy combined with the random forest (RF) algorithm was proposed for the classification of ten iron ore samples.


Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1241
Author(s):  
Nikolaos Gyftokostas ◽  
Eleni Nanou ◽  
Dimitrios Stefas ◽  
Vasileios Kokkinos ◽  
Christos Bouras ◽  
...  

In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.


2021 ◽  
Vol 129 (10) ◽  
pp. 1336
Author(s):  
Sonali Dubey ◽  
Rohit Kumar ◽  
Abhishek K. Rai ◽  
Awadhesh K. Rai

Laser-induced breakdown spectroscopy (LIBS) is emerging as an analytical tool for investigating geological materials. The unique abilities of this technique proven its potential in the area of geology. Detection of light elements, portability for in-field analysis, spot detection, and no sample preparation are some features that make this technique appropriate for the study of geological materials. The application of the LIBS technique has been tremendously developed in recent years. In this report, results obtained from previous and most recent studies regarding the investigation of geological materials LIBS technique are reviewed. Firstly, we introduce investigations that report the advancement in LIBS instrumentation, its applications, especially in the area of gemology and the extraterrestrial/planetary exploration have been reviewed. Investigation of gemstones by LIBS technique is not widely reviewed in the past as compared to LIBS application in planetary exploration or other geological applications. It is anticipated that for the classification of gemstones samples, huge data set is appropriate and to analyze this data set, multivariate/chemometric methods will be useful. Recent advancement of LIBS instrumentation for the study of meteorites, depth penetration in Martian rocks and its regolith proved the feasibility of LIBS used as robotic vehicles in the Martian environment. Keywords: LIBS, Gemstone, geological samples, Extra-terrestrial


2018 ◽  
Vol 33 (3) ◽  
pp. 461-467 ◽  
Author(s):  
W. T. Li ◽  
Y. N. Zhu ◽  
X. Li ◽  
Z. Q. Hao ◽  
L. B. Guo ◽  
...  

The ASPI-LDA algorithm combined with a compact spectrometer to achieve high accuracy classification, which has a great potential for field in situ remote detection.


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