Due to the complexity of terrain and climate in the mountain–plain transition zone, it is
difficult to simulate and forecast the flow discharge of river basins accurately. The poor …

This study aims to develop a smart model for carrying out two-dimensional (2D) inundation
simulation by estimating the gridded inundation depths via the ANN-derived models …

Inundation mapping by flood simulation is subject to uncertainties which spatial accuracy
assessment could not be processed as normal mapping does. This paper presents a …

This study proposes a stochastic artificial neural network (named ANN_GA-SA_MTF), in
which the parameters of the multiple transfer functions considered are calibrated by the …

In response to the increasing threats of flash flooding, how to generate flood maps in real
time has drawn great attention. In this study, a hybrid ML model was developed for flood …

Flooding is the main disaster type in Taiwan and is usually caused by typhoons and heavy
rainfall. To understand the flood impacts in Taiwan caused by increasing rainfall due to …

This study aims to develop a smart model for the two-dimensional (2D) inundation
simulation based on the derived artificial neural network (ANN) model with real-time …

This study aims to develop a smart model for evaluating the spatial density of added IoT
sensors (called AIOT grids) to optimize their amount and placements, named …

This paper aims to develop a stochastic model (SM_EID_IOT) for estimating the inundation
depths and associated 95% confidence intervals at the specific locations of the roadside …

In this study, we proposed and tested a method based on system response curve (SRC) to
extract the error information of areal mean rainfall. These extracted rainfall error are then …