Automated Flare Prediction Using Extreme Learning Machine
Joint Authors
Li, Ming
Bian, Yuqing
Lan, Rushi
Yang, Jianwei
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-29
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Extreme learning machine (ELM) is a fast learning algorithm of single-hidden layer feedforward neural networks (SLFNs).
Compared with the traditional neural networks, the ELM algorithm has the advantages of fast learning speed and good generalization.
At the same time, an ordinal logistic regression (LR) is a statistical method which is conceptually simple and algorithmically fast.
In this paper, in order to improve the real-time performance, a flare forecasting method is introduced which is the combination of the LR model and the ELM algorithm.
The predictive variables are three photospheric magnetic parameters, that is, the total unsigned magnetic flux, length of the strong-gradient magnetic polarity inversion line, and total magnetic energy dissipation.
The LR model is used to map these three magnetic parameters of each active region into four probabilities.
Consequently, the ELM is used to map the four probabilities into a binary label which is the final output.
The proposed model is used to predict the occurrence of flares with a certain level over 24 hours following the time when the magnetogram is recorded.
The experimental results show that the cascade algorithm not only improves learning speed to realize timely prediction but also has higher accuracy of X-class flare prediction in comparison with other methods.
American Psychological Association (APA)
Bian, Yuqing& Yang, Jianwei& Li, Ming& Lan, Rushi. 2013. Automated Flare Prediction Using Extreme Learning Machine. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1032453
Modern Language Association (MLA)
Bian, Yuqing…[et al.]. Automated Flare Prediction Using Extreme Learning Machine. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1032453
American Medical Association (AMA)
Bian, Yuqing& Yang, Jianwei& Li, Ming& Lan, Rushi. Automated Flare Prediction Using Extreme Learning Machine. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1032453
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032453