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 …
Index-based groundwater vulnerability map** models using hydrogeological settings: a critical evaluation
Groundwater vulnerability maps are useful for decision making in land use planning and
water resource management. This paper reviews the various groundwater vulnerability …
water resource management. This paper reviews the various groundwater vulnerability …
Evaluation of groundwater quality and its suitability for drinking and irrigation using GIS and geostatistics techniques in semiarid region of Neyshabur, Iran
Groundwater is a vital source for drinking and agricultural purposes in semiarid region of
Neyshabur area (Iran). The present study assessed the groundwater quality and mapped …
Neyshabur area (Iran). The present study assessed the groundwater quality and mapped …
[HTML][HTML] Assessment of groundwater nitrate pollution using the Indicator Kriging approach
G Balacco, GD Fiorese, MR Alfio - Groundwater for Sustainable …, 2023 - Elsevier
This paper presents the results of investigations on groundwater nitrate pollution to assess
its spatial and temporal evolution through the indicator kriging method. With this approach …
its spatial and temporal evolution through the indicator kriging method. With this approach …
[BOOK][B] Arsenic in groundwater: poisoning and risk assessment
MM Hassan - 2018 - taylorfrancis.com
Arsenic-contaminated groundwater is considered one of the world's largest environmental
health crises, as more than 300 million people in more than one-third of countries worldwide …
health crises, as more than 300 million people in more than one-third of countries worldwide …
Categorical Indicator Kriging for assessing the risk of groundwater nitrate pollution: the case of Vega de Granada aquifer (SE Spain)
Groundwater nitrate pollution associated with agricultural activity is an important
environmental problem in the management of this natural resource, as acknowledged by the …
environmental problem in the management of this natural resource, as acknowledged by the …
[HTML][HTML] Predictive map** of soil electrical conductivity as a Proxy of soil salinity in south-east of Algeria
In semi-arid and arid areas soil salinity has adverse effects both on the environment and
agricultural production. The region of Biskra (South-East of Algeria) underwent a strong …
agricultural production. The region of Biskra (South-East of Algeria) underwent a strong …
Spatial distribution of heavy metals in soils of the flood plain of the Seversky Donets River (Russia) based on geostatistical methods
VG Linnik, TV Bauer, TM Minkina… - Environmental …, 2022 - Springer
Soil contamination by heavy metals (HM) is a worldwide problem for human health. To
reduce risk to human health from exposure to toxic chemicals associated with soil …
reduce risk to human health from exposure to toxic chemicals associated with soil …
[HTML][HTML] Residual geochemical gold grade prediction using extreme gradient boosting
The increasing cost of exploration and decreasing recovery in mineral exploration
necessitates the use of reliable and robust models for spatial gold grade prediction. In …
necessitates the use of reliable and robust models for spatial gold grade prediction. In …
Spatial assessment of groundwater quality monitoring wells using indicator kriging and risk map**, Amol-Babol Plain, Iran
The main aim of monitoring wells is to assess the conditions of groundwater quality in the
aquifer system. An inappropriate distribution of sampling wells could produce insufficient or …
aquifer system. An inappropriate distribution of sampling wells could produce insufficient or …