Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review
With the rapid development of electric vehicles, the safe and environmentally friendly
disposal of retired lithium batteries (LIBs) is becoming a serious issue. Echelon utilization of …
disposal of retired lithium batteries (LIBs) is becoming a serious issue. Echelon utilization of …
[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 …
[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 …
COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach
Several epidemiological models are being used around the world to project the number of
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous …
Heavy rainfall in mountainous terrain can trigger numerous landslides in hill slopes. These
landslides can be deadly to the community living downslope with their fast pace, turning …
landslides can be deadly to the community living downslope with their fast pace, turning …
[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
Assessment of long and short-term flood risk using the multi-criteria analysis model with the AHP-Entropy method in Poyang Lake basin
J Wu, X Chen, J Lu - International Journal of Disaster Risk Reduction, 2022 - Elsevier
China suffers the most serious loss of life and property with the most floods in the world. In
this study, a multi-criteria analysis model with the combined analytic hierarchy process and …
this study, a multi-criteria analysis model with the combined analytic hierarchy process and …
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 …