Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines
V Rodriguez-Galiano, M Sanchez-Castillo… - Ore Geology …, 2015 - Elsevier
Abstract Machine learning algorithms (MLAs) such us artificial neural networks (ANNs),
regression trees (RTs), random forest (RF) and support vector machines (SVMs) are …
regression trees (RTs), random forest (RF) and support vector machines (SVMs) are …
Multi-and hyperspectral geologic remote sensing: A review
Geologists have used remote sensing data since the advent of the technology for regional
map**, structural interpretation and to aid in prospecting for ores and hydrocarbons. This …
map**, structural interpretation and to aid in prospecting for ores and hydrocarbons. This …
[BOOK][B] Geochemical anomaly and mineral prospectivity map** in GIS
EJM Carranza - 2008 - books.google.com
Geochemical Anomaly and Mineral Prospectivity Map** in GIS documents and explains,
in three parts, geochemical anomaly and mineral prospectivity map** by using a …
in three parts, geochemical anomaly and mineral prospectivity map** by using a …
Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran
HR Pourghasemi, N Kerle - Environmental earth sciences, 2016 - Springer
In many parts of the world, landslide susceptibility remains inadequately mapped, due to the
lack of both data and suitable methods for widespread implementation. Iran is one of those …
lack of both data and suitable methods for widespread implementation. Iran is one of those …
[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 …
Flood spatial modeling in northern Iran using remote sensing and gis: A comparison between evidential belief functions and its ensemble with a multivariate logistic …
Floods are some of the most dangerous and most frequent natural disasters occurring in the
northern region of Iran. Flooding in this area frequently leads to major urban, financial …
northern region of Iran. Flooding in this area frequently leads to major urban, financial …
A novel scheme for map** of MVT-type Pb–Zn prospectivity: LightGBM, a highly efficient gradient boosting decision tree machine learning algorithm
The gradient boosting decision tree is a well-known machine learning algorithm. Despite
numerous advancements in its application, its efficiency still needs to be improved for large …
numerous advancements in its application, its efficiency still needs to be improved for large …
Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models
DT Bui, B Pradhan, O Lofman, I Revhaug, OB Dick - Catena, 2012 - Elsevier
The main objective of this study is to evaluate and compare the results of evidential belief
functions and fuzzy logic models for spatial prediction of landslide hazards in the Hoa Binh …
functions and fuzzy logic models for spatial prediction of landslide hazards in the Hoa Binh …
A comparative assessment between three machine learning models and their performance comparison by bivariate and multivariate statistical methods in …
As demand for fresh groundwater in the worldwide is increasing, delineation of groundwater
spring potential zones become an increasingly important tool for implementing a successful …
spring potential zones become an increasingly important tool for implementing a successful …
Data-driven predictive modelling of mineral prospectivity using machine learning and deep learning methods: A case study from southern Jiangxi Province, China
T Sun, H Li, K Wu, F Chen, Z Zhu, Z Hu - Minerals, 2020 - mdpi.com
Predictive modelling of mineral prospectivity, a critical, but challenging procedure for
delineation of undiscovered prospective targets in mineral exploration, has been spurred by …
delineation of undiscovered prospective targets in mineral exploration, has been spurred by …