GIS-based statistical model for the prediction of flood hazard susceptibility
At present, flood is the most significant environmental problem in the entire world. In this
work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of …
work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of …
Impact of climate change on future flood susceptibility: an evaluation based on deep learning algorithms and GCM model
Floods are common and recurring natural hazards which damages is the destruction for
society. Several regions of the world with different climatic conditions face the challenge of …
society. Several regions of the world with different climatic conditions face the challenge of …
Detection of areas prone to flood risk using state-of-the-art machine learning models
The present study aims to evaluate the susceptibility to floods in the river basin of Buzau in
Romania through the following 6 machine learning models: Support Vector Machine (SVM) …
Romania through the following 6 machine learning models: Support Vector Machine (SVM) …
Modeling reference evapotranspiration using a novel regression-based method: radial basis M5 model tree
In the current study, an ability of a novel regression-based method is evaluated in modeling
daily reference evapotranspiration (ET0), which is an important issue in water resources …
daily reference evapotranspiration (ET0), which is an important issue in water resources …
Deep learning algorithms to develop Flood susceptibility map in Data-Scarce and Ungauged River Basin in India
Flood is considered the most extensive natural disaster around the globe. Kunur River, a
riverine landscape of Rarh Bengal, was selected as the study area because this basin has …
riverine landscape of Rarh Bengal, was selected as the study area because this basin has …
Novel Bayesian additive regression tree methodology for flood susceptibility modeling
Identifying areas prone to flooding is a key step in flood risk management. The purpose of
this study is to develop and present a novel flood susceptibility model based on Bayesian …
this study is to develop and present a novel flood susceptibility model based on Bayesian …
[HTML][HTML] Flash flood and landslide susceptibility analysis for a mountainous roadway in Vietnam using spatial modeling
Flash floods and landslides are dangerous natural hazards in hilly areas. They often occur
extensively and potentially cause widespread destruction to agriculture, infrastructure …
extensively and potentially cause widespread destruction to agriculture, infrastructure …
Machine learning-enabled regional multi-hazards risk assessment considering social vulnerability
The regional multi-hazards risk assessment poses difficulties due to data access challenges,
and the potential interactions between multi-hazards and social vulnerability. For better …
and the potential interactions between multi-hazards and social vulnerability. For better …
Investigation of ANN architecture for predicting shear strength of fiber reinforcement bars concrete beams
In this paper, an extensive simulation program is conducted to find out the optimal ANN
model to predict the shear strength of fiber-reinforced polymer (FRP) concrete beams …
model to predict the shear strength of fiber-reinforced polymer (FRP) concrete beams …
Hybrid models based on deep learning neural network and optimization algorithms for the spatial prediction of tropical forest fire susceptibility in Nghe An province …
HD Nguyen - Geocarto International, 2022 - Taylor & Francis
The main objective of this study was to produce forest fire susceptibility maps in the Nghe An
province of Vietnam using machine learning models and GIS, namely Deep Neural Network …
province of Vietnam using machine learning models and GIS, namely Deep Neural Network …