Artificial intelligence for mineral exploration: A review and perspectives on future directions from data science
The massive accumulation of available multi-modal mineral exploration data for most
metallogenic belts worldwide provides abundant information for the discovery of mineral …
metallogenic belts worldwide provides abundant information for the discovery of mineral …
Data analysis methods for prospectivity modelling as applied to mineral exploration targeting: State-of-the-art and outlook
Mineral exploration targeting is a highly complex decision-making task. Two key risk factors,
the quality of exploration data and robustness of the underlying conceptual targeting model …
the quality of exploration data and robustness of the underlying conceptual targeting model …
Translation of the function of hydrothermal mineralization-related focused fluid flux into a mappable exploration criterion for mineral exploration targeting
Formation of hydrothermal mineralization is related to the late stages of, or immediate
following, orogenic compressional regimes that have been superimposed on arc …
following, orogenic compressional regimes that have been superimposed on arc …
Geodata science-based mineral prospectivity map**: A review
R Zuo - Natural Resources Research, 2020 - Springer
This paper introduces the concept of geodata science-based mineral prospectivity map**
(GSMPM), which is based on analyzing the spatial associations between geological …
(GSMPM), which is based on analyzing the spatial associations between geological …
Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid …
The support vector classifier (SVC) is one of the most powerful machine learning algorithms.
This algorithm has been accepted as an effective method in three-dimensional geological …
This algorithm has been accepted as an effective method in three-dimensional geological …
Supervised mineral exploration targeting and the challenges with the selection of deposit and non-deposit sites thereof
Selection of non-deposit sites is a challenging issue affecting the application of supervised
algorithms for modeling mineral exploration targets. For this, equal number of deposit and …
algorithms for modeling mineral exploration targets. For this, equal number of deposit and …
Polymetallic mineralization prospectivity modelling using multi-geospatial data in logistic regression: The Diapiric Zone, Northeastern Algeria
Prospecting and exploring minerals present major challenges in tectonically complex
regions for sustainable development as in Northeastern Algeria. This area is promising for …
regions for sustainable development as in Northeastern Algeria. This area is promising for …
[HTML][HTML] Overcoming survival bias in targeting mineral deposits of the future: Towards null and negative tests of the exploration search space, accounting for lack of …
Broad consensus exists amongst mineral explorers that most outcrop** mineral deposits
have been found. The next generation of discoveries will rely on our ability to recognize the …
have been found. The next generation of discoveries will rely on our ability to recognize the …
[HTML][HTML] Mitigating uncertainties in mineral exploration targeting: Majority voting and confidence index approaches in the context of an exploration information system …
Various mineral prospectivity modelling (MPM) approaches are available for targeting
mineral deposits, each method capable of predicting areas of high prospectivity. Given the …
mineral deposits, each method capable of predicting areas of high prospectivity. Given the …