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 …
[HTML][HTML] Comprehensive overview of flood modeling approaches: A review of recent advances
As one of nature's most destructive calamities, floods cause fatalities, property destruction,
and infrastructure damage, affecting millions of people worldwide. Due to its ability to …
and infrastructure damage, affecting millions of people worldwide. Due to its ability to …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
ARMT Islam, S Talukdar, S Mahato, S Kundu… - Geoscience …, 2021 - Elsevier
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
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 …
Hydrogeochemical evaluation of groundwater aquifers and associated health hazard risk mapping using ensemble data driven model in a water scares plateau region …
Health hazard risk mapping (HHRM) is an important technique used to estimate the potential
health risk of an individual, a group, or an entire community of a region. To further progress …
health risk of an individual, a group, or an entire community of a region. To further progress …
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
The flooding in Bangladesh during monsoon season is very common and frequently
happens. Consequently, people have been experiencing tremendous damage to properties …
happens. Consequently, people have been experiencing tremendous damage to properties …
[HTML][HTML] Flash flood susceptibility modeling using new approaches of hybrid and ensemble tree-based machine learning algorithms
Flash flooding is considered one of the most dynamic natural disasters for which measures
need to be taken to minimize economic damages, adverse effects, and consequences by …
need to be taken to minimize economic damages, adverse effects, and consequences by …
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
Flood risk assessment is an important task for disaster management activities in flood-prone
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques
HA Afan, A Ibrahem Ahmed Osman… - Engineering …, 2021 - Taylor & Francis
This study proposes two techniques: Deep Learning (DL) and Ensemble Deep Learning
(EDL) to predict groundwater level (GWL) for five wells in Malaysia. Two scenarios were …
(EDL) to predict groundwater level (GWL) for five wells in Malaysia. Two scenarios were …
Ensemble models of GLM, FDA, MARS, and RF for flood and erosion susceptibility mapping: a priority assessment of sub-basins
The mountainous watersheds are increasingly challenged with extreme erosions and
devastating floods due to climate change and human interventions. Hazard mapping is …
devastating floods due to climate change and human interventions. Hazard mapping is …