Forecasting Ionospheric foF2 Using Bidirectional LSTM and Attention Mechanism

The critical frequency of ionospheric F2 layer (foF2) is an important ionospheric characteristic parameter. In this paper, a deep learning model based on Bidirectional long short‐term memory (BiLSTM) and attention mechanism is implemented for predicting the foF2 parameter. The inputs of models are t...

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Veröffentlicht in:	Space Weather 2023-11, Vol.21 (11), p.n/a
Hauptverfasser:	Tang, Jun, Yang, Dengpan, Ding, Mingfei
Format:	Artikel
Sprache:	eng
Schlagworte:	attention mechanism BiLSTM Correlation coefficient Correlation coefficients F 2 region foF2 forecasting Geomagnetic activity Geomagnetic storms Geomagnetism Ionosondes Ionosphere Ionospheric forecasting Ionospheric models Latitude Longitude LSTM Magnetic storms Mathematical models Modelling Parameters Performance prediction Prediction models Root-mean-square errors Seasons Solar activity Winter
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