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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 …
A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration
Geochemical survey data provide rich information on geochemical elemental concentrations
and their spatial patterns in relation to mineralization or pollution. A geochemical data cube …
and their spatial patterns in relation to mineralization or pollution. A geochemical data cube …
[HTML][HTML] Combination of machine learning algorithms with concentration-area fractal method for soil geochemical anomaly detection in sediment-hosted Irankuh Pb-Zn …
Prediction of geochemical concentration values is essential in mineral exploration as it plays
a principal role in the economic section. In this paper, four regression machine learning (ML) …
a principal role in the economic section. In this paper, four regression machine learning (ML) …
Big data analytics of identifying geochemical anomalies supported by machine learning methods
Big data analytics brings a novel way for identifying geochemical anomalies in mineral
exploration because it involves processing of the whole geochemical dataset to reveal …
exploration because it involves processing of the whole geochemical dataset to reveal …
Recognizing multivariate geochemical anomalies for mineral exploration by combining deep learning and one-class support vector machine
The recognition of multivariate geochemical anomalies is important for mineral exploration.
Big data analytics, which involves the whole data and variables, is an alternative manner to …
Big data analytics, which involves the whole data and variables, is an alternative manner to …
Recognition of geochemical anomalies using a deep variational autoencoder network
Deep learning (DL) algorithms have received increased attention in various fields. In the
field of geoscience, DL has been shown to be a powerful tool for mining complex, high-level …
field of geoscience, DL has been shown to be a powerful tool for mining complex, high-level …
Application of one-class support vector machine to quickly identify multivariate anomalies from geochemical exploration data
Y Chen, W Wu - Geochemistry: Exploration, Environment, Analysis, 2017 - lyellcollection.org
Identifying multivariate anomalies from geochemical exploration data in a complex
geological setting is very challenging because the complex geological setting may lead to …
geological setting is very challenging because the complex geological setting may lead to …
A machine learning method for distinguishing detrital zircon provenance
Zircon geochemistry provides a sensitive monitor of its parental magma composition.
However, due to the complexity of the uptake of trace elements during zircon growth …
However, due to the complexity of the uptake of trace elements during zircon growth …