Low Tropospheric Wind Forecasts in Aviation: The Potential of Deep Learning for Terminal Aerodrome Forecast Bulletins
Décio Alves,
Fábio Mendonça,
Sheikh Shanawaz Mostafa
et al.
Abstract:In aviation, accurate wind prediction is crucial, especially during takeoff and landing at complex sites like Gran Canaria Airport. This study evaluated five Deep Learning models: Long Short-Term Memory (LSTM), Vanilla Recurrent Neural Network (vRNN), One-Dimensional Convolutional Neural Network (1dCNN), Convolutional Neural Network Long Short-Term Memory (CNN-LSTM), and Gated Recurrent Unit (GRU) for forecasting wind speed and direction. The LSTM model demonstrated the highest precision, particularly for exte… Show more
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