Objectives Identifying an appropriate set of predictors for the outcome of interest is a major
challenge in clinical prediction research. The aim of this study was to show the application of …

Predictive analytics utilizing machine learning algorithms play a pivotal role in various
domains, including the profiling of carbon dioxide (CO2) emissions. This research paper …

Reliable water quality prediction can improve environmental flow monitoring and the
sustainability of the stream ecosystem. In this study, we compared two machine learning …

Abstract Statistical downscaling of Global Climate Models (GCMs) allows researchers to
study local climate change effects decades into the future. A wide range of statistical models …

Regional climate models are essential for climate change projections and hydrologic
modelling studies, especially in watersheds that are overly sensitive to changes in climate …

Abstract General Circulation Models (GCMs) provide vital information on the likely future
climate, much needed for the effective planning and management of water resources. The …

A reliable and accurate extreme air temperature in summer is necessary to prepare for and
respond to thermal disasters such as heatstroke and power outages. The numerical weather …

River water temperature is essential in regulating many physical and biochemical processes
in river systems. Consequently, it is crucial to develop reliable tools for predicting extreme …

A timely and accurate estimation of body weight in finishing pigs is critical in determining
profits by allowing pork producers to make informed marketing decisions on group-housed …

Wind speed estimation at ungauged locations is one of the preliminary steps for wind
resource assessment. With the availability of high-resolution Digital Elevation Models (DEM) …