The role of factors affecting flood hazard zoning using analytical hierarchy process: a review
Flood hazard zoning is an important problem that has received much attention from
environmental researchers. This problem requires complex spatial analysis; hence …
environmental researchers. This problem requires complex spatial analysis; hence …
Flood hazard assessment and mapping using GIS integrated with multi-criteria decision analysis in upper Awash River basin, Ethiopia
Floods have destroyed people's lives as well as social and environmental assets. Flooding
is becoming more severe and frequent as a result of climate change and an increase in …
is becoming more severe and frequent as a result of climate change and an increase in …
Comparison of machine learning algorithms for flood susceptibility mapping
Floods are one of the most destructive natural disasters, causing financial and human losses
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
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 …
Integrating machine learning and geospatial data analysis for comprehensive flood hazard assessment
Flooding is a major natural hazard worldwide, causing catastrophic damage to communities
and infrastructure. Due to climate change exacerbating extreme weather events robust flood …
and infrastructure. Due to climate change exacerbating extreme weather events robust flood …
[HTML][HTML] Assessing multi-climate-hazard threat in the coastal region of Bangladesh by combining influential environmental and anthropogenic factors
This study developed a geo-spatial framework for assessing multi-hazard threat on the
Bangladesh coast, integrating environmental hazards (EH), geo-environmental attributes …
Bangladesh coast, integrating environmental hazards (EH), geo-environmental attributes …
Sustainable flood risk assessment using deep learning-based algorithms with a blockchain technology
MU Mia, M Rahman, A Elbeltagi… - Geocarto …, 2022 - Taylor & Francis
The couplings of convolutional neural networks (CNN) with random forest (RF), support
vector machine (SVM), long short-term memory (LSTM), and extreme gradient boosting …
vector machine (SVM), long short-term memory (LSTM), and extreme gradient boosting …
Climatic and hydrological factors affecting the assessment of flood hazards and resilience using modified UNDRR indicators: Ayutthaya, Thailand
P Munpa, S Kittipongvises, A Phetrak… - Water, 2022 - mdpi.com
This research aims to investigate the effect of climatic and hydrological factors on flood
hazards and assess flood resilience in Ayutthaya, Thailand, using the 10 essentials for …
hazards and assess flood resilience in Ayutthaya, Thailand, using the 10 essentials for …
Flood susceptibility modeling using an advanced deep learning-based iterative classifier optimizer
MU Mia, TN Chowdhury, R Chakrabortty, SC Pal… - Land, 2023 - mdpi.com
We developed a novel iterative classifier optimizer (ICO) with alternating decision tree
(ADT), naïve Bayes (NB), artificial neural network (ANN), and deep learning neural network …
(ADT), naïve Bayes (NB), artificial neural network (ANN), and deep learning neural network …