Enhancing mineral prospectivity mapping with geospatial artificial intelligence: A geographically neural network-weighted logistic regression approach
Accurate prediction of mineral resources is imperative to meet the energy demands of modern society. Nonetheless, this task is often difficult due to estimation bias and limited interpretability of conventional statistical techniques and machine learning methods. To address these shortcomings, we pr...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-04-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224001006 |