Floods are one of the most perilous natural calamities that cause property destruction and
endanger human life. The spatial patterns of flood susceptibility were assessed in this study …

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 …

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 …

Globally, many studies on machine learning (ML)-based flood susceptibility modeling have
been carried out in recent years. While majority of those models produce reasonably …

Floods are among the most devastating environmental hazards that directly and indirectly
affect people's lives and activities. In many countries, sustainable environmental …

Flood is considered one of the most dangerous natural disasters among all-natural
disasters. Prediction of flood susceptible areas is a primary task for adopting management …

Floods are one of the most destructive natural disasters causing financial damages and
casualties every year worldwide. Recently, the combination of data‐driven techniques with …

The largest recorded flood loss occurred in the study area in 2013. This study aims to
examine resampling methods (ie cross-validation (CV), bootstrap, and random …

Flood is one of the most devastating natural disasters with socio-economic and
environmental consequences. Thus, comprehensive flood management is essential to …

Machine learning algorithms are becoming more and more popular in natural disaster
assessment. Although the technology has been tested in flood susceptibility analysis of …