Isolation Forest as an Alternative Data-Driven Mineral Prospectivity Mapping Method with a Higher Data-Processing Efficiency
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science
Link
http://link.springer.com/article/10.1007/s11053-018-9375-6/fulltext.html
Reference85 articles.
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2. Abedi, M., Norouzi, G. H., & Bahroudi, A. (2012a). Support vector machine for multi-classification of mineral prospectivity areas. Computers and Geosciences, 46(2), 272–283.
3. Abedi, M., Torabi, S. A., Norouzi, G. H., & Hamzeh, M. (2012b). ELECTRE III: A knowledge-driven method for integration of geophysical data with geological and geochemical data in mineral prospectivity mapping. Journal of Applied Geophysics, 87(12), 9–18.
4. Abedi, M., Torabi, S. A., Norouzi, G. H., Hamzeh, M., & Elyasi, G. R. (2012c). PROMETHEE II: A knowledge-driven method for copper exploration. Computers and Geosciences, 46(2), 255–263.
5. Agterberg, F. P. (1974). Automatic contouring of geological maps to detect target areas for mineral exploration. Mathematical Geology, 6(4), 373–395.
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