Unsupervised Machine Learning for Lithological Mapping Using Geochemical Data in Covered Areas of Jining, China
- 5 January 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Natural Resources Research
- Vol. 30 (2), 1053-1068
- https://doi.org/10.1007/s11053-020-09788-z
Abstract
No abstract availableKeywords
Funding Information
- National Key Research and Development Program of China (Nos. 2016YFC0600508 and 2016YFC0600501)
- National Natural Science Foundation of China (Nos. 41972305 and 41430320)
- Chinese Geological Survey Project (Nos. DD20160045 and DD20190459)
This publication has 64 references indexed in Scilit:
- A study of the lake sediment geochemistry of the Melville Peninsula using multivariate methods: Applications for predictive geological mappingJournal of Geochemical Exploration, 2014
- Essentials of the self-organizing mapNeural Networks, 2013
- Application of geochemical anomaly identification methods in mapping of intermediate and felsic igneous rocks in eastern Tianshan, ChinaJournal of Geochemical Exploration, 2012
- Clustering of mineral prospectivity area as an unsupervised classification approach to explore copper depositArabian Journal of Geosciences, 2012
- Support vector machine: A tool for mapping mineral prospectivityComputers & Geosciences, 2011
- Analysis and integration of geo-information to identify granitic intrusions as exploration targets in southeastern Yunnan District, ChinaComputers & Geosciences, 2011
- Assembly, accretion, and break-up of the Palaeo-Mesoproterozoic Columbia supercontinent: record in the North China Craton revisitedInternational Geology Review, 2011
- Timing of Paleoproterozoic ultrahigh-temperature metamorphism in the North China Craton: Evidence from SHRIMP U–Pb zircon geochronologyPrecambrian Research, 2007
- Principles of Data MiningDrug Safety, 2007
- Compositional data and their analysis: an introductionGeological Society, London, Special Publications, 2006