Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques
S Saravanan, D Abijith - Geocarto International, 2022 - Taylor & Francis
Flooding is one of the most challenging and important natural disasters to predict, it is
becoming more frequent and more intense. The study area is badly damaged by devastating …
becoming more frequent and more intense. The study area is badly damaged by devastating …
Flood susceptibility assessment of the Agartala Urban Watershed, India, using machine learning algorithm
Frequent floods are a severe threat to the well-being of people the world over. This is
particularly severe in developing countries like India where tropical monsoon climate …
particularly severe in developing countries like India where tropical monsoon climate …
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 …
A comparison of performance measures of three machine learning algorithms for flood susceptibility mapping of river Silabati (tropical river, India)
Flood is the most common phenomenon causing extensive disruption to the environment,
socio-economy, infrastructure and many other aspects of human life. Flood susceptibility …
socio-economy, infrastructure and many other aspects of human life. Flood susceptibility …
Flood susceptibility mapping in Brahmaputra floodplain of Bangladesh using deep boost, deep learning neural network, and artificial neural network
Floods are considered one of the most destructive natural hydro-meteorological disasters
across the world. The present study attempts to assess flood susceptibility of the …
across the world. The present study attempts to assess flood susceptibility of the …
Flood susceptibility mapping using machine learning boosting algorithms techniques in Idukki district of Kerala India
Kerala experiences a high rate of annual rainfall and flooding resulting in a frequent natural
disaster. The objective of this study is to develop flood susceptibility maps for the Idukki …
disaster. The objective of this study is to develop flood susceptibility maps for the Idukki …
Use of machine learning algorithms to assess flood susceptibility in the coastal area of Bangladesh
The geographical location of Bangladesh makes it quite vulnerable to natural disasters.
Flooding is one of those disasters. The coastal area of Bangladesh has higher vulnerability …
Flooding is one of those disasters. The coastal area of Bangladesh has higher vulnerability …
Study of hybridized support vector regression based flood susceptibility mapping for Bangladesh
Flooding has become an exceedingly complex problem in many developing countries of the
world including Bangladesh. Currently, Bangladesh is using MIKE 11 hydrodynamic model …
world including Bangladesh. Currently, Bangladesh is using MIKE 11 hydrodynamic model …
Evaluation of machine learning, information theory and multi-criteria decision analysis methods for flood susceptibility mapping under varying spatial scale of analyses
The annual average economic losses due to various natural disasters are increasing
exponentially across the globe and have reached a mark of US $239.2 billion per year …
exponentially across the globe and have reached a mark of US $239.2 billion per year …
Flood susceptibility mapping in an arid region of Pakistan through ensemble machine learning model
A Yaseen, J Lu, X Chen - Stochastic Environmental Research and Risk …, 2022 - Springer
Floods are among the most destructive natural hazards. Therefore, their prediction is pivotal
for flood management and public safety. Factors contributing to flood are different for every …
for flood management and public safety. Factors contributing to flood are different for every …