[HTML][HTML] GIS-based mineral prospectivity map** using machine learning methods: A case study from Tongling ore district, eastern China
T Sun, F Chen, L Zhong, W Liu, Y Wang - Ore Geology Reviews, 2019 - Elsevier
Predictive modelling of mineral prospectivity using GIS is a valid and progressively more
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …
Exploration information systems–A proposal for the future use of GIS in mineral exploration targeting
The advent of modern data collection and storage technologies has brought about a huge
increase in data volumes with both traditional and machine learning tools struggling to …
increase in data volumes with both traditional and machine learning tools struggling to …
Stacking: A novel data-driven ensemble machine learning strategy for prediction and map** of Pb-Zn prospectivity in Varcheh district, west Iran
Various ensemble machine learning techniques have been widely studied and implemented
to construct the predictive models in different sciences, including bagging, boosting, and …
to construct the predictive models in different sciences, including bagging, boosting, and …
Prediction–area (P–A) plot and C–A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling
There are methods of mineral prospectivity map** whereby, besides assignment of
weights to classes of evidence in an evidential map, every evidential map is also given a …
weights to classes of evidence in an evidential map, every evidential map is also given a …
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 …
Novel soft computing model for predicting blast-induced ground vibration in open-pit mines based on particle swarm optimization and XGBoost
X Zhang, H Nguyen, XN Bui, QH Tran… - Natural Resources …, 2020 - Springer
Blasting is a useful technique for rocks fragmentation in open-pit mines, underground mines,
as well as for civil engineering work. However, the negative impacts of blasting, especially …
as well as for civil engineering work. However, the negative impacts of blasting, especially …
A convolutional neural network of GoogLeNet applied in mineral prospectivity prediction based on multi-source geoinformation
N Yang, Z Zhang, J Yang, Z Hong, J Shi - Natural Resources Research, 2021 - Springer
The traditional convolutional neural networks applied in mineral prospectivity map**
usually extract features from only one scale at each iteration, resulting in plain features. To …
usually extract features from only one scale at each iteration, resulting in plain features. To …
Data-driven logistic-based weighting of geochemical and geological evidence layers in mineral prospectivity map**
In mineral prospectivity map** (MPM) logistic functions have been widely used to
transform mineral exploration data or prospectivity values into the [0, 1] range to generate …
transform mineral exploration data or prospectivity values into the [0, 1] range to generate …
Applications of data augmentation in mineral prospectivity prediction based on convolutional neural networks
N Yang, Z Zhang, J Yang, Z Hong - Computers & geosciences, 2022 - Elsevier
The supervised deep learning methods applied in mineral prospectivity map** usually
need sufficient samples for training models. However, mineralization is a rare event …
need sufficient samples for training models. However, mineralization is a rare event …