In this paper we propose and discuss different Deep Learning-based ensemble algorithms
for a problem of low-visibility events prediction due to fog. Specifically, seven different Deep …

To mitigate haze impacts, three visibility simulation schemes were designed using decision
tree and random forest algorithms, leveraging atmospheric boundary layer meteorological …

In this paper, we propose different explicable forecasting approaches, based on inductive
and evolutionary decision rules, for extreme low-visibility events prediction. Explicability of …

In this study, we aimed to estimate cloud cover with high accuracy using images from a
camera-based imager and a convolutional neural network (CNN) as a potential alternative …

Abstract Changes in evapotranspiration can affect water availability and climate, leading to
extreme weather and severe impact on ecosystems. In particular, increased water stress in …

Air quality issues, including health and environmental challenges, have recently become
more relevant in urban areas with large populations and active industries. Therefore …

Introduction: This study presents the application of machine learning (ML) to evaluate
marine fog visibility conditions and nowcasting of visibility based on the FATIMA (Fog and …

Regional visibility forecasting encounters challenges due to data imbalance, temporal non‐
linearity and the consideration of multi‐scale spatial factors. To tackle these challenges, this …

This study utilizes six years of hourly meteorological data from seven observation stations in
the Beibu Gulf—Qinzhou (QZ), Fangcheng (FC), Beihai (BH), Fangchenggang (FCG) …

This study aims to provide an efficient and accurate model by comparing the tree-based
machine learning approach and the global prediction model with the European Center for …