Artificial neural network approaches for disaster management: A literature review
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
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 …
Prediction of groundwater quality using efficient machine learning technique
To ensure safe drinking water sources in the future, it is imperative to understand the quality
and pollution level of existing groundwater. The prediction of water quality with high …
and pollution level of existing groundwater. The prediction of water quality with high …
[HTML][HTML] Evaluating urban flood risk using hybrid method of TOPSIS and machine learning
With the growth of cities, urban flooding has increasingly become an issue for regional and
national governments. The destructive effects of floods are magnified in cities. Accurate …
national governments. The destructive effects of floods are magnified in cities. Accurate …
GIS-based comparative assessment of flood susceptibility map** using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
Flood risk assessment is an important task for disaster management activities in flood-prone
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
The exponential growth in the number of flash flood events is a global threat, and detecting a
flood-prone area has also become a top priority. The flash flood-susceptibility map** can …
flood-prone area has also become a top priority. The flash flood-susceptibility map** can …
[HTML][HTML] Flood susceptibility map** using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Map** flood-prone areas is an important part of flood disaster management. In this study …
Map** flood-prone areas is an important part of flood disaster management. In this study …
[HTML][HTML] Urban flood modeling using deep-learning approaches in Seoul, South Korea
Identification of flood-prone sites in urban environments is necessary, but there is insufficient
hydraulic information and time series data on surface runoff. To date, several attempts have …
hydraulic information and time series data on surface runoff. To date, several attempts have …
Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran
Iran experiences frequent destructive floods with significant socioeconomic consequences.
Quantifying the accurate impacts of such natural hazards, however, is a complicated task …
Quantifying the accurate impacts of such natural hazards, however, is a complicated task …