Tag: mineral prospectivity mapping

A case study of the Damiao–Hongshila belt shows geographically weighted models improve mineral prospectivity mapping under spatially non-stationary conditions.

Researchers developed a data-uncertainty-aware and explainable 3D mineral prospectivity mapping framework, trialed in China's Wulong gold district, that estimates prospectivity ...

A transfer learning method tested in Iran's Kerman magmatic arc identified all three known porphyry copper deposits in an evaluation ...

Researchers combined positive-unlabeled learning, spatial block cross-validation, bootstrap uncertainty, and conformal calibration to produce a confidence-aware nickel prospectivity map of ...

A machine-learning model that scored near-perfectly on a Chinese lead–zinc deposit collapsed when tested across a mirror-inverted fault system, revealing ...

New research shows that coarse, smoothed labels in continental-scale AI mineral prospectivity maps artificially inflate model performance while erasing high-probability ...

A validated weighted-overlay prospectivity model, built from resistivity and magnetic data along Ethiopia's western Afar rift margin, captured all known ...

A new framework combining geological constraints and point pattern analysis shows that the choice of non-deposit training locations can dramatically ...

Researchers at the University of Ghana used random forest and decision tree classifiers trained on airborne geophysical data to map ...

Researchers at Shandong University of Technology show that convolutional neural networks, especially AlexNet, can map gold prospectivity at the Jinchang ...