[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] Flood susceptibility zonation using advanced ensemble machine learning models within Himalayan foreland basin
S Ghosh, S Saha, B Bera - Natural Hazards Research, 2022 - Elsevier
Floods are considered as one of nature's most destructive fluvio-hydrological extremes
because of the massive damage to agricultural land, roads and buildings and human …
because of the massive damage to agricultural land, roads and buildings and human …
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 …
Flood susceptibility modeling in a subtropical humid low-relief alluvial plain environment: application of novel ensemble machine learning approach
This study has developed a new ensemble model and tested another ensemble model for
flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two …
flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two …
[HTML][HTML] Gis-based machine learning algorithm for flood susceptibility analysis in the Pagla river basin, Eastern India
The unique characteristics of drainage conditions in the Pagla river basin cause flooding
and harm the socioeconomic environment. The main purpose of this study is to investigate …
and harm the socioeconomic environment. The main purpose of this study is to investigate …
Modeling spatial flood using novel ensemble artificial intelligence approaches in northern Iran
The uncertainty of flash flood makes them highly difficult to predict through conventional
models. The physical hydrologic models of flash flood prediction of any large area is very …
models. The physical hydrologic models of flash flood prediction of any large area is very …
Computational machine learning approach for flood susceptibility assessment integrated with remote sensing and GIS techniques from Jeddah, Saudi Arabia
Floods, one of the most common natural hazards globally, are challenging to anticipate and
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
Novel ensemble machine learning models in flood susceptibility mapping
The research aims to propose the new ensemble models by combining the machine
learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k …
learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k …
Prediction success of machine learning methods for flash flood susceptibility mapping in the Tafresh watershed, Iran
Floods are some of the most destructive and catastrophic disasters worldwide. Development
of management plans needs a deep understanding of the likelihood and magnitude of future …
of management plans needs a deep understanding of the likelihood and magnitude of future …
[HTML][HTML] A novel approach for flood hazard assessment using hybridized ensemble models and feature selection algorithms
Identifying flood-prone regions is critical for effective management of flood hazards as floods
are among the most devastating natural disasters globally. However, accurate modeling and …
are among the most devastating natural disasters globally. However, accurate modeling and …