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Solar flare forecasting using sunspot-groups classification and photospheric magnetic parameters

Published online by Cambridge University Press:  26 August 2011

Yuan Yuan ,
Frank Y. Shih ,
Ju Jing  and
Haimin Wang
Yuan Yuan
Affiliation:
Space Weather Research Lab, New Jersey Institute of Technology, 323 MLK Blvd, Newark, New Jersey, United States email: yy46@njit.edu Computer Vision Lab, New Jersey Institute of Technology, 323 MLK Blvd, Newark, New Jersey, United States
Frank Y. Shih
Affiliation:
Computer Vision Lab, New Jersey Institute of Technology, 323 MLK Blvd, Newark, New Jersey, United States
Ju Jing
Affiliation:
Space Weather Research Lab, New Jersey Institute of Technology, 323 MLK Blvd, Newark, New Jersey, United States email: yy46@njit.edu
Haimin Wang
Affiliation:
Space Weather Research Lab, New Jersey Institute of Technology, 323 MLK Blvd, Newark, New Jersey, United States email: yy46@njit.edu
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Abstract

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In this paper, we investigate whether incorporating sunspot-groups classification information would further improve the performance of our previous logistic regression based solar flare forecasting method, which uses only line-of-sight photospheric magnetic parameters. A dataset containing 4913 samples from the year 2000 to 2005 is constructed, in which 2721 samples from the year 2000, 2002 and 2004 are used as a training set, and the remaining 2192 samples from the year 2001, 2003 and 2005 are used as a testing set. Experimental results show that sunspot-groups classification combined with total gradient on the strong gradient polarity neutral line achieve the highest forecasting accuracy and thus it testifies sunspot-groups classification does help in solar flare forecasting.

Keywords

Sun: flaressun: magnetic fieldssunspots
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 6 , Symposium S273: The Physics of Sun and Star Spots , August 2010 , pp. 446 - 450
Copyright
Copyright © International Astronomical Union 2011

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