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Study on intelligent discrimination of tectonic settings based on global gabbro data from GEOROC
Jiao ShouTao1,2,3; Zhou YongZhang1,2,3; Zhang Qi4; Jin WeiJun4; Liu YanPeng1,2,3; Wang Jun1,2,3
2018
Source PublicationACTA PETROLOGICA SINICA
ISSN1000-0569
Volume34Issue:11Pages:3189-3194
AbstractThe study of discrimination diagrams began in the 1970s. The basalt tectonic environmental discriminant diagrams are the most commonly used in academic circles and have achieved very good results. With the accumulation of data, many scholars have gradually discovered the limitations of the discriminating diagrams and tried to establish new discrimination diagrams with better effect. The gabbro is an intrusive rock with a chemical composition similar to that of basalt. The predecessors thought that the formation process of gabbro was too complicated. The magma may have undergone fractional crystallization, mixing, hybridization, and it cannot be used to determine the tectonic setting formed by magmatic rocks. In this paper, the data mining of gabbro was studied using the data from the database of Geochemistry of Rocks of the Oceans and Continents (GEOROC), and three different algorithms of machine learning (Support Vector Machine, K Nearest Neighbor, and Random Forest) were used for gabbro. The intelligent discriminant research for tectonic settings, compared with the previous discrimination diagrams, has obtained a better discriminant effect. The random forest method has the best effect, and the judgment accuracy rate can reach 97%. Therefore, it is considered that the geochemical data of gabbro can be used to determine the tectonic setting of magmatic rocks. Based on the existing results, the random forest algorithm has the best effect.
KeywordGabbro Machine learning Data mining SVM Random forest GEOROC Python
WOS KeywordVOLCANIC-ROCKS ; N-MORB ; CLASSIFICATION ; GEOCHEMISTRY ; DIAGRAMS
Language英语
WOS Research AreaGeology
WOS SubjectGeology
WOS IDWOS:000456929100004
PublisherSCIENCE PRESS
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/90207
Collection其他部门
Corresponding AuthorJiao ShouTao
Affiliation1.Sun Yat Sen Univ, Res Ctr Earth Environm & Resources, Guangzhou 510275, Guangdong, Peoples R China
2.Sun Yat Sen Univ, Sch Earth Sci & Engn, Guangzhou 510275, Guangdong, Peoples R China
3.Guangdong Prov Key Lab Geol Proc & Mineral Resour, Guangzhou 510275, Guangdong, Peoples R China
4.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China
Recommended Citation
GB/T 7714
Jiao ShouTao,Zhou YongZhang,Zhang Qi,et al. Study on intelligent discrimination of tectonic settings based on global gabbro data from GEOROC[J]. ACTA PETROLOGICA SINICA,2018,34(11):3189-3194.
APA Jiao ShouTao,Zhou YongZhang,Zhang Qi,Jin WeiJun,Liu YanPeng,&Wang Jun.(2018).Study on intelligent discrimination of tectonic settings based on global gabbro data from GEOROC.ACTA PETROLOGICA SINICA,34(11),3189-3194.
MLA Jiao ShouTao,et al."Study on intelligent discrimination of tectonic settings based on global gabbro data from GEOROC".ACTA PETROLOGICA SINICA 34.11(2018):3189-3194.
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