Predicting Solar Flares Using SDO/HMI Vector Magnetic Data Products and the Random Forest Algorithm

Astrophysical Journal

Volumn 843, Issue 2, 2017, Pages

  Liu, Chang ^a,b   Deng, Na ^a,b   Wang, Jason T L ^c   Wang, Haimin ^a,b  

^a NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

^b NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

^c University Heights   (United States)

Author keywords

magnetic fields; Sun: activity; Sun: flares

Indexed keywords

EID: 85025151429     PISSN: 0004637X     EISSN: 15384357     Source Type: Journal    
DOI: 10.3847/1538-4357/aa789b     Document Type: Article

References (44)

1. Abramenko V. I. 2005 ApJ 629 1141
2. Ahmed O. W., Qahwaji R., Colak T. et al 2013 SoPh 283 157
3. Bailey S., Aragon C., Romano R. et al 2007 ApJ 665 1246
4. Barnes G. and Leka K. D. 2008 ApJL 688 L107
5. Barnes G., Leka K. D., Schrijver C. J. et al 2016 ApJ 829 89
6. Barnes G., Leka K. D., Schumer E. A. and Della-Rose D. J. 2007 SpWea 5 S09002
7. Bloomfield D. S., Higgins P. A., McAteer R. T. J. and Gallagher P. T. 2012 ApJL 747 L41
8. Bobra M. G. and Couvidat S. 2015 ApJ 798 135
9. Bobra M. G., Sun X., Hoeksema J. T. et al 2014 SoPh 289 3549
10. Breiman L. 2001 Machine Learning 45 5
11. Breiman L., Friedman J. H., Olshen R. A. and Stone C. J. 1984 Classification and Regression Trees (Monterey, CA: Wadsworth and Brooks)
12. Breiman L., Last M. and Rice J. 2003 Random Forests: Finding Quasars (New York: Springer) 243
13. Carliles S., Budavári T., Heinis S., Priebe C. and Szalay A. S. 2010 ApJ 712 511
14. Daglis I., Baker D., Kappenman J., Panasyuk M. and Daly E. 2004 SpWea 2 S02004
15. Denig W., Green J., Rodriguez J. and Viereck R. 2012 COSPAR Meeting 39, 39th COSPAR Scientific Assembly 442
16. Farrell S. A., Murphy T. and Lo K. K. 2015 ApJ 813 28
17. Fisher G. H., Bercik D. J., Welsch B. T. and Hudson H. S. 2012 SoPh 277 59
18. Gallagher P. T., Moon Y.-J. and Wang H. 2002 SoPh 209 171
19. Geurts P., Ernst D. and Wehenkel L. 2006 Mach. Learn 63 3
20. Guyon I. and Elisseeff A. 2003 J. Mach. Learn. Res. 3 1157
21. Hanssen A. W. and Kuipers W. J. A. 1965 Meded, Verh 81 2
22. Hodge K. A. 2014 PhD thesis California Institute of Technology
23. James G., Witten D., Hastie T. and Tibshirani R. 2013 An Introduction to Statistical Learning: With Applications in R (Berlin: Springer)
24. Japkowicz N. and Stephen S. 2002 Intell. Data Anal. 6 429
25. Kuhn M. 2008 Journal of Statistical Software 28 1
26. Laing C., Wen D., Wang J. T. L. and Schlick T. 2012 Nucleic Acids Research 40 487
27. Leka K. D. and Barnes G. 2003 ApJ 595 1296
28. Leka K. D. and Barnes G. 2007 ApJ 656 1173
29. Liaw A. and Wiener M. 2002 R News 2 18
30. Liu C., Liu R., Xu Y. and Wang H. 2010 BAAS 41 403.10
31. Meyer D., Dimitriadou E., Hornik K., Weingessel A. and Leisch F. 2017 e1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), r package version 1.6-8 (Vienna: TU Wien)
32. Nishizuka N., Sugiura K., Kubo Y. et al 2017 ApJ 835 156
33. Pesnell W. D., Thompson B. J. and Chamberlin P. C. 2012 SoPh 275 3
34. Priest E. R. and Forbes T. G. 2002 A&ARv 10 313
35. R Core Team 2016 R: A Language and Environment for Statistical Computing (Vienna, Austria: R Foundation for Statistical Computing)
36. Schou J., Scherrer P. H., Bush R. I. et al 2012 SoPh 275 229
37. Schrijver C. J. 2007 ApJL 655 L117
38. Song H., Tan C., Jing J. et al 2009 SoPh 254 101
39. Sun X. and for the CGEM Team 2014 arXiv:1405.7353
40. Wang H. and Liu C. 2015 RAA 15 145
41. Welsch B. T., Li Y., Schuck P. W. and Fisher G. H. 2009 ApJ 705 821
42. Woodcock F. 1976 MWRv 104 1209
43. Yuan Y., Shih F. Y., Jing J. and Wang H.-M. 2010 RAA 10 785
44. Zhao Y. and Cen Y. (ed) 2013 Data Mining Applications with R (New York, Amsterdam: Academic, Elsevier)