Ensemble machine learning paradigms in hydrology: A review
Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
A review of ensemble learning algorithms used in remote sensing applications
Y Zhang, J Liu, W Shen - Applied Sciences, 2022 - mdpi.com
Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …
Flood hazard mapping methods: A review
Flood hazard mapping (FHM) has undergone significant development in terms of approach
and capacity of the result to meet the target of policymakers for accurate prediction and …
and capacity of the result to meet the target of policymakers for accurate prediction and …
[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory
TG Nachappa, ST Piralilou, K Gholamnia… - Journal of …, 2020 - Elsevier
Floods are one of the most widespread natural hazards occurring across the globe. The
main objective of this study was to produce flood susceptibility maps for the province of …
main objective of this study was to produce flood susceptibility maps for the province of …
A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods
Floods around the world are having devastating effects on human life and property. In this
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees
R Abedi, R Costache… - Geocarto …, 2022 - Taylor & Francis
Historical exploration of flash flood events and producing flash-flood susceptibility maps are
crucial steps for decision makers in disaster management. In this article, classification and …
crucial steps for decision makers in disaster management. In this article, classification and …
[HTML][HTML] Predicting flood susceptibility using LSTM neural networks
Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …
makers to prevent and manage disasters. Plenty of studies have used machine learning …
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
Floods are one of the most damaging natural hazards causing huge loss of property,
infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due …
infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due …
GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …