[HTML][HTML] Groundwater potential mapping combining artificial neural network and real AdaBoost ensemble technique: the DakNong province case-study, Vietnam
The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Quadratic discriminant analysis based ensemble machine learning models for groundwater potential modeling and mapping
DH Ha, PT Nguyen, R Costache, N Al-Ansari… - Water Resources …, 2021 - Springer
In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Ensemble boosting and bagging based machine learning models for groundwater potential prediction
Due to the rapidly increasing demand for groundwater, as one of the principal freshwater
resources, there is an urge to advance novel prediction systems to more accurately estimate …
resources, there is an urge to advance novel prediction systems to more accurately estimate …
Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential
Y Chen, W Chen, S Chandra Pal, A Saha… - Geocarto …, 2022 - Taylor & Francis
Delineation of the groundwater's potential zones is a growing phenomenon worldwide due
to the high demand for fresh groundwater. Therefore, the identification of potential …
to the high demand for fresh groundwater. Therefore, the identification of potential …
[HTML][HTML] Soft computing ensemble models based on logistic regression for groundwater potential mapping
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
[HTML][HTML] Groundwater potentiality mapping using ensemble machine learning algorithms for sustainable groundwater management
Purpose The present study aims to construct ensemble machine learning (EML) algorithms
for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh …
for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh …
Groundwater potential mapping in the Central Highlands of Vietnam using spatially explicit machine learning
The sustainability of water resource management remains challenging in many regions
around the world. Yet while the significance of groundwater potential maps in water …
around the world. Yet while the significance of groundwater potential maps in water …
Groundwater aquifer potential modeling using an ensemble multi-adoptive boosting logistic regression technique
Abstract Machine learning and data-driven models have achieved a favorable reputation in
the field of advanced geospatial modeling, particularly for models of groundwater aquifer …
the field of advanced geospatial modeling, particularly for models of groundwater aquifer …
Groundwater potential mapping in hubei region of china using machine learning, ensemble learning, deep learning and automl methods
Z Bai, Q Liu, Y Liu - Natural Resources Research, 2022 - Springer
Freshwater scarcity has become more widespread on a global scale in recent years. Surface
water resources are no longer sufficient to meet the demands of human productivity and …
water resources are no longer sufficient to meet the demands of human productivity and …
The effect of sample size on different machine learning models for groundwater potential mapping in mountain bedrock aquifers
Abstract Machine learning models have attracted much research attention for groundwater
potential mapping. However, the accuracy of models for groundwater potential mapping is …
potential mapping. However, the accuracy of models for groundwater potential mapping is …