… machine learning models with flood risk … risk and the driving factors are crucial for improving
flood management. In this study, six machine learning models were utilized for flood risk …

… the proposed approach would be effective for flood risk management in the study area along
the … the flood risk level in a study area that is affected by annual flooding. An appropriate …

… flood risks prediction based on CRISP-DM methodology using BN and three machine learning
(… The aims of this research is to develop a predictive modelling for flood risks prediction in …

… analytics of flood risks with emphasis on flood data clustering… effectively visualize, classify
and predict flood risks. In addition, to … for classification and prediction of flood risks, benefits the …

… traditional flood risks with hydrology and hydraulic factors but to identify flood risks using
vulnerability and hazard indicators. The traditional approach to preparing flood-risk maps is to …

… decision-making and machine learning tools in urban flood risk assessment We summarize
… the machine learning algorithms of SVM, RF, and BRT to provide urban flood hazard maps …

… In Romania, like in any other European country, the flood risk management activity must be
… the flood risk management should be based primarily on the detection of areas prone to flood …

… to prevent urban flood damage. In this study, a flood risk map was produced with limited
hydrological and hydraulic data using two state-of-the-art machine learning models: Genetic …

… in flood risk assessment, it is important that machine learning implementations are transparent
and supervised by independent machine learning and flood risk assessment experts. …

… flooding occurs across most climate zones. Owing to the lack of appropriate infrastructures
and applicable predictive methods, flooding … -priority flood risk areas using machine learning (…