Deep learning and its application in geochemical mapping
Abstract Machine learning algorithms have been applied widely in the fields of natural
science, social science and engineering. It can be expected that machine learning …
science, social science and engineering. It can be expected that machine learning …
The processing methods of geochemical exploration data: past, present, and future
Geochemical exploration data is popular in mineral exploration in that it plays a notable role
in discovering unknown mineral deposits. In this study, we review the state-of-the-art popular …
in discovering unknown mineral deposits. In this study, we review the state-of-the-art popular …
[HTML][HTML] Ensemble learning models with a Bayesian optimization algorithm for mineral prospectivity mapping
J Yin, N Li - Ore geology reviews, 2022 - Elsevier
Abstract Machine learning algorithms have been widely applied in mineral prospectivity
mapping (MPM). In this study, we implemented ensemble learning of extreme gradient …
mapping (MPM). In this study, we implemented ensemble learning of extreme gradient …
Machine learning of mineralization-related geochemical anomalies: A review of potential methods
R Zuo - Natural Resources Research, 2017 - Springer
Research on processing geochemical data and identifying geochemical anomalies has
made important progress in recent decades. Fractal/multi-fractal models, compositional data …
made important progress in recent decades. Fractal/multi-fractal models, compositional data …
Quantification of uncertainty associated with evidence layers in mineral prospectivity mapping using direct sampling and convolutional neural network
Mineral prospectivity mapping (MPM) mainly focuses on searching prospective areas for a
particular type of mineral deposits. However, MPM is typically subject to uncertainties …
particular type of mineral deposits. However, MPM is typically subject to uncertainties …
Visualization and interpretation of geochemical exploration data using GIS and machine learning methods
Geochemical exploration has provided significant clues for mineral exploration and has
helped discover many mineral deposits. Although various methods, including classic …
helped discover many mineral deposits. Although various methods, including classic …
A comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas
Fractal/multifractal modeling of geochemical data is an interesting topic in the field of applied
geochemistry. Identification of weak anomalies for mineral exploration in covered areas is …
geochemistry. Identification of weak anomalies for mineral exploration in covered areas is …
Identification of heavy metal pollution sources and its associated risk assessment in an industrial town using the K-means clustering technique
N Khorshidi, M Parsa, DR Lentz, J Sobhanverdi - Applied Geochemistry, 2021 - Elsevier
This study intends to (i) identify the potential sources of heavy metal (HM) pollution in an
industrial town situated in the northwestern part of Iran and (ii) and assess whether the …
industrial town situated in the northwestern part of Iran and (ii) and assess whether the …
Evaluation of uncertainty in mineral prospectivity mapping due to missing evidence: a case study with skarn-type Fe deposits in Southwestern Fujian Province, China
In this paper, the southwestern Fujian metallogenic belt, one of the important Fe polymetallic
belts in southern China, was chosen as a case study area to evaluate the uncertainty due to …
belts in southern China, was chosen as a case study area to evaluate the uncertainty due to …
Identification of weak anomalies: A multifractal perspective
Attention has increasingly been focused on weak geochemical anomalies. In this paper, the
singularity mapping technique, a powerful multifractal tool to identify weak anomalies, is …
singularity mapping technique, a powerful multifractal tool to identify weak anomalies, is …