The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
Flood prediction and uncertainty estimation using deep learning
Floods are a complex phenomenon that are difficult to predict because of their non-linear
and dynamic nature. Therefore, flood prediction has been a key research topic in the field of …
and dynamic nature. Therefore, flood prediction has been a key research topic in the field of …
Deep learning methods for flood mapping: a review of existing applications and future research directions
Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …
the limitations of accurate, yet slow, numerical models, and to improve the results of …
Designing deep-based learning flood forecast model with ConvLSTM hybrid algorithm
Efficient, robust, and accurate early flood warning is a pivotal decision support tool that can
help save lives and protect the infrastructure in natural disasters. This research builds a …
help save lives and protect the infrastructure in natural disasters. This research builds a …
Data‐driven flood emulation: Speeding up urban flood predictions by deep convolutional neural networks
Z Guo, JP Leitao, NE Simões… - Journal of Flood Risk …, 2021 - Wiley Online Library
Computational complexity has been the bottleneck for applying physically based simulations
in large urban areas with high spatial resolution for efficient and systematic flooding …
in large urban areas with high spatial resolution for efficient and systematic flooding …
Decentralized flood forecasting using deep neural networks
Predicting flood for any location at times of extreme storms is a longstanding problem that
has utmost importance in emergency management. Conventional methods that aim to …
has utmost importance in emergency management. Conventional methods that aim to …
An intelligent early flood forecasting and prediction leveraging machine and deep learning algorithms with advanced alert system
Flood disasters are a natural occurrence around the world, resulting in numerous casualties.
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
[HTML][HTML] Deep learning neural networks for spatially explicit prediction of flash flood probability
Flood probability maps are essential for a range of applications, including land use planning
and developing mitigation strategies and early warning systems. This study describes the …
and developing mitigation strategies and early warning systems. This study describes the …
Water level forecasting using deep learning time-series analysis: A case study of red river of the north
The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
A short-term flood prediction based on spatial deep learning network: A case study for Xi County, China
Floods cause substantial damage across the world every year. Accurate and timely
prediction of floods can significantly minimize the loss of life and property. Recently …
prediction of floods can significantly minimize the loss of life and property. Recently …