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 …
Decision support tools, systems and indices for sustainable coastal planning and management: A review
Coasts worldwide are facing enormous challenges relating to extreme water levels,
inundation and coastal erosion. These challenges need to be addressed with consideration …
inundation and coastal erosion. These challenges need to be addressed with consideration …
Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis
The present study was done in order to simulate the flash-flood susceptibility across the
Suha river basin in Romania using a number of 3 hybrid models and fuzzy-AHP multicriteria …
Suha river basin in Romania using a number of 3 hybrid models and fuzzy-AHP multicriteria …
Towards better flood risk management: Assessing flood risk and investigating the potential mechanism based on machine learning models
J Chen, G Huang, W Chen - Journal of environmental management, 2021 - Elsevier
Integrating powerful machine learning models with flood risk assessment and determining
the potential mechanism between risk and the driving factors are crucial for improving flood …
the potential mechanism between risk and the driving factors are crucial for improving flood …
Flood hazards susceptibility mapping using statistical, fuzzy logic, and MCDM methods
H Akay - Soft Computing, 2021 - Springer
In this study, the flood hazards susceptibility map of an area in Turkey which is frequently
exposed to flooding was predicted by training 70% of inventory data. For this, statistical, and …
exposed to flooding was predicted by training 70% of inventory data. For this, statistical, and …
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 …
Computational machine learning approach for flood susceptibility assessment integrated with remote sensing and GIS techniques from Jeddah, Saudi Arabia
Floods, one of the most common natural hazards globally, are challenging to anticipate and
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms
Flood is considered as the most devastating natural hazards that cause the death of many
lives worldwide. The present study aimed to predict flood vulnerability for Warsaw, Poland …
lives worldwide. The present study aimed to predict flood vulnerability for Warsaw, Poland …
GIS-based hybrid machine learning for flood susceptibility prediction in the Nhat Le–Kien Giang watershed, Vietnam
HD Nguyen - Earth Science Informatics, 2022 - Springer
Floods is a natural hazard that occurs over a short time with a high transmission speed.
Flood risk management in many countries employs flood susceptibility modeling to mitigate …
Flood risk management in many countries employs flood susceptibility modeling to mitigate …
Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India)
RT Vilasan, VS Kapse - Natural Hazards, 2022 - Springer
Floods are one of the frequent natural hazards occurring in Kerala because of the
remarkably high annual rate of rainfall. The objective of this study is to prepare the flood …
remarkably high annual rate of rainfall. The objective of this study is to prepare the flood …