Prediction of soft proton intensities in the near-Earth space using machine learning

Prediction of soft proton intensities in the near-Earth space using machine learning

These files are the saved model weights for prediction of channels 1-5, and add that they can be loaded by import joblib model = joblib.load("channel_p1.joblib")

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Bibliographische Detailangaben
Hauptverfasser: Kronberg, Elena A., Hannan, Tanveer, Huthmacher, Jens, Münzer, Marcus, Peste, Florian, Zhou, Ziyang, Berrendorf, Max, Faerman, Evgeniy
Format: Dataset
Sprache:eng
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Beschreibung
Zusammenfassung:These files are the saved model weights for prediction of channels 1-5, and add that they can be loaded by import joblib model = joblib.load("channel_p1.joblib")
DOI:10.5281/zenodo.4593064