Physical Sciences → Computer Science → Artificial Intelligence
Geochemistry and Geologic Mapping
This cluster of papers focuses on the application of machine learning, remote sensing, and compositional data analysis techniques for mineral prospectivity mapping. It explores the use of advanced technologies such as ASTER and hyperspectral imaging to identify geological features, geochemical anomalies, and hydrothermal alterations associated with mineralization. The cluster also delves into the challenges and opportunities in using support vector machines, fractal modeling, and statistical analysis for predicting undiscovered mineral deposits.
4M works worldwide1.7M citations
Machine LearningMineral ProspectivityRemote SensingCompositional Data AnalysisGeological MappingHyperspectral ImagingSupport Vector MachinesFractal ModelingGeochemical AnomaliesLithological Mapping
Journals publishing in this area
20

International Journal of Cloud Computing and Database Management
ISSN 2707-59073 articles in this topic
3h-index
0.23Impact
147Articles
49Citations


.jpg)



