Solar Flare Predictive Features Derived from Polarity Inversion Line Masks in Active Regions Using an Unsupervised Machine Learning Algorithm

The properties of the polarity inversion line (PIL) in solar active regions (ARs) are strongly correlated to flare occurrences. The PIL mask, enclosing the PIL areas, has shown significant potential for improving machine-learning-based flare prediction models. In this study, an unsupervised machine-...

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Bibliographic Details

Published in:	The Astrophysical journal Vol. 892; no. 2; pp. 140 - 148
Main Authors:	Wang, Jingjing, Zhang, Yuhang, Hess Webber, Shea A., Liu, Siqing, Meng, Xuejie, Wang, Tieyan
Format:	Journal Article
Language:	English
Published:	Philadelphia The American Astronomical Society 01.04.2020 IOP Publishing
Subjects:	Algorithms Astrophysics Classification Forest management Machine learning Masks Polarity Prediction models Principal components analysis Solar active regions Solar activity Solar activity regions Solar flares Space weather Unsupervised learning
ISSN:	0004-637X, 1538-4357
Online Access:	Get full text
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