In, a multiobjective evolutionary neural network was applied to the same problem, obtaining improvements over alternative ML algorithms.
In, different ML regression approaches were tested in the problem of low-visibility events prediction due to radiation fog at Valladolid airport, Spain. For example, in, artificial neural networks (ANNs) were used to provide accurate forecasts at Canberra International Airport, employing a 44-year database of standard meteorological observations. Many of these approaches were, in fact, proposed in the frame of transportation safety, and many of them were tested with airports or roads data. As part of data-driven approaches, machine learning (ML) and deep learning (DL) approaches have become an attractive tool to tackle the prediction of low-visibility events, obtaining a level of accuracy not seen before.
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