Discrimination of rocks by laser-induced breakdown spectroscopy combined with Random Forest (RF). Issue 1 (5th December 2022)

• Record Type: Journal Article
• Authors: Jin, Xueying; Yang, Guang; Sun, Xuxu; Qu, Dongming; Li, Shichao; Chen, Guanyu; Li, Chunsheng; Tian, Di; Yao, Li
• Is Part Of: Journal of analytical atomic spectrometry. Volume 38:Issue 1(2023)
• Page Start: 243
• Page End: 252
• Publication Date: 2022-12-05
• Subjects: Atomic spectra -- Periodicals; Atomic absorption spectroscopy -- Periodicals; 543.0858
• DOI: 10.1039/d2ja00290f
• Languages: English
• ISSNs: 0267-9477

Abstract

Abstract : LIBS and RF were combined to realize the discrimination of rocks from different provenances. Abstract : The great significance of geological research is to serve the development of society and economy. Laser-Induced Breakdown Spectroscopy (LIBS), a simple but efficient spectral analysis method, has advantages over traditional analysis methods. LIBS provides convenience for the exploration of geological resources. In this research, LIBS and Random Forest (RF) algorithm were combined for discriminating the provenance and lithology of rock samples from the Dajianggang area of Shuangyang and the Chaihe area of Daxing'anling. Four RF models were established to realize the discrimination of the provenance. The results showed that the model established by the preprocessing and variable selection of data has the best discrimination performance, and the accuracy reached 97.78%. The RF was also used to analyse the lithology of rock samples from the two areas. The classification accuracy of rock samples from the Dajianggang area was 100%, while that of rock samples from the Chaihe area was only 76.67% after optimization. The experimental results showed that the RF algorithm can effectively discriminate the provenance of rock and present more advantages in discriminating lithology of rocks with obvious characteristics in content.