Prediction of the Dst Index with Bagging Ensemble-learning Algorithm

The Dst index is a commonly geomagnetic index used to measure the strength of geomagnetic activity. The accurate prediction of the Dst index is one of the main subjects of space weather studies. In this study, we use the Bagging ensemble-learning algorithm, which combines three algorithms-the artifi...

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Veröffentlicht in:	The Astrophysical journal. Supplement series Jg. 248; H. 1; S. 14 - 24
Hauptverfasser:	Xu, S. B., Huang, S. Y., Yuan, Z. G., Deng, X. H., Jiang, K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Saskatoon The American Astronomical Society 01.05.2020 IOP Publishing
Schlagworte:	Accuracy Algorithms Artificial neural networks Bagging Correlation coefficient Correlation coefficients DST Index Electric fields Ensemble learning Geomagnetic activity Geomagnetic fields Geomagnetism Machine learning Magnetic fields Magnetic storms Model accuracy Neural networks Planetary magnetosphere Plasma temperature Root-mean-square errors Solar wind Solar wind parameters Solar wind velocity Space weather Storm forecasting Support vector machines Wind speed
ISSN:	0067-0049, 1538-4365
Online-Zugang:	Volltext
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