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 …
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] Flood susceptibility modelling using advanced ensemble machine learning models
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 …
[HTML][HTML] Evaluating urban flood risk using hybrid method of TOPSIS and machine learning
With the growth of cities, urban flooding has increasingly become an issue for regional and
national governments. The destructive effects of floods are magnified in cities. Accurate …
national governments. The destructive effects of floods are magnified in cities. Accurate …
[HTML][HTML] Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area
Forest fire disaster is currently the subject of intense research worldwide. The development
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
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 …
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …
and management in both the short and long terms. Despite of some studies using machine …
Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method
Flash-floods are increasingly recognized as a frequent natural hazard worldwide. Iran has
been among the most devastated regions affected by the major floods. While the temporal …
been among the most devastated regions affected by the major floods. While the temporal …