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March 3, 2026
Prospectivity Mapping of Targets for Li-Bearing Pegmatites and Granites in Västernorrland, Sweden, with Fuzzy Logic and Random Forest Modeling
SJ
Saleha Javed
Luleå University of Technology
EC
Emmanuel John M. Carranza
MS
Martiya Sadeghi
Key Points
Lithium-bearing pegmatites were mapped effectively, enhancing exploration efficiency.
Using random forest modeling, the analysis achieved an accuracy of 85% in predicting targets.
The study employs fuzzy logic combined with machine learning to improve prediction reliability.
Significant geographical areas for future exploration are highlighted, suggesting potential economic benefits.
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Javed et al. (Sat,) studied this question.
synapsesocial.com/papers/69a75a23c6e9836116a1fb2b
https://doi.org/https://doi.org/10.1007/s11053-025-10633-4
Prospectivity Mapping of Targets for Li-Bearing Pegmatites and Granites in Västernorrland, Sweden, with Fuzzy Logic and Random Forest Modeling | Synapse