Solar Physics

, Volume 262, Issue 2, pp 511–539 | Cite as

Machine Leaning-Based Investigation of the Associations between CMEs and Filaments

  • M. Al-Omari
  • R. QahwajiEmail author
  • T. Colak
  • S. Ipson


In this work we study the association between eruptive filaments/prominences and coronal mass ejections (CMEs) using machine learning-based algorithms that analyse the solar data available between January 1996 and December 2001. The support vector machine (SVM) learning algorithm is used for the purpose of knowledge extraction from the association results. The aim is to identify patterns of associations that can be represented using SVM learning rules for the subsequent use in near real-time and reliable CME prediction systems. Timing and location data in the US National Geophysical Data Center (NGDC) filament catalogue and the Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph (SOHO/LASCO) CME catalogue are processed to associate filaments with CMEs. In the previous studies, which classified CMEs into gradual and impulsive CMEs, the associations were refined based on the CME speed and acceleration. Then the associated pairs were refined manually to increase the accuracy of the training dataset. In the current study, a data-mining system is created to process and associate filament and CME data, which are arranged in numerical training vectors. Then the data are fed to SVMs to extract the embedded knowledge and provide the learning rules that can have the potential, in the future, to provide automated predictions of CMEs. The features representing the event time (average of the start and end times), duration, type, and extent of the filaments are extracted from all the associated and not-associated filaments and converted to a numerical format that is suitable for SVM use. Several validation and verification methods are used on the extracted dataset to determine if CMEs can be predicted solely and efficiently based on the associated filaments. More than 14 000 experiments are carried out to optimise the SVM and determine the input features that provide the best performance.


Coronal mass ejections Filaments Machine learning Prominences Space weather 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Al-Omari, M., Qahwaji, R., Colak, T., Ipson, S.: 2008, In: Saleem, A.I., Barakat, S. (eds.) 5th International Multi-Conference on Systems, Signals and Devices (IEEE SSD 2008), 1. Google Scholar
  2. Aschwanden, M.J.: 2004, Physics of the Solar Corona: An Introduction, Praxis Publishing, Chichester, 704. Google Scholar
  3. Balch, C.C.: 2008, Space Weather 6, S01001. CrossRefGoogle Scholar
  4. Briand, C.: 2003, Astron. Nachr. 324, 357. ADSCrossRefGoogle Scholar
  5. Cliver, E.W., Hudson, H.S.: 2002, J. Atmos. Solar-Terr. Phys. 64, 231. ADSCrossRefGoogle Scholar
  6. Fawcett, T.: 2006, Pattern Recognit. Lett. 27, 861. CrossRefGoogle Scholar
  7. Freund, Y., Schapire, R.E.: 1996, In: Blum, A., Kearns, M. (eds.) Proc. Ninth Annual Conference on Computational Learning Theory, 325. Google Scholar
  8. Freund, Y., Schapire, R.E.: 1997, J. Comput. Syst. Sci. 55, 119. MathSciNetzbMATHCrossRefGoogle Scholar
  9. Friedman, J., Hastie, T., Tibshirani, R.: 2000, Ann. Stat. 38, 337. MathSciNetCrossRefGoogle Scholar
  10. Fukunaga, K.: 1990, Introduction to Statistical Pattern Recognition, Academic Press, New York. zbMATHGoogle Scholar
  11. Gilbert, H.R., Holzer, T.E., Burkepile, J.T., Hundhausen, A.J.: 2000, Astrophys. J. 537, 503. ADSCrossRefGoogle Scholar
  12. Gopalswamy, N., Shimojo, M., Lu, W., Yashiro, S., Shibasaki, K., Howard, R.A.: 2003, Astrophys. J. 586, 562. ADSCrossRefGoogle Scholar
  13. Gopalswamy, N., Yashiro, S., Michalek, G., Stenborg, G., Vourlidas, A., Freeland, S., Howard, R.: 2009, Earth, Moon, Planets 104, 295. ADSCrossRefGoogle Scholar
  14. Heidke, P.: 1926, Geograf. Ann. 8, 301. CrossRefGoogle Scholar
  15. Hori, K., Culhane, J.L.: 2002, Astron. Astrophys. 382, 666. ADSCrossRefGoogle Scholar
  16. Jing, J.: 2005, Dynamics of filaments, flares and coronal mass ejections (CMEs). Ph.D. Thesis, State University of New Jersey, Newark, New Jersey. Google Scholar
  17. Jing, J., Yang, G., Wang, H.M.: 2003, Bull. Am. Astron. Soc. 35, 815. ADSGoogle Scholar
  18. Jing, J., Yurchyshyn, V.B., Yang, G., Xu, Y., Wang, H.: 2004, Astrophys. J. 614, 1054. ADSCrossRefGoogle Scholar
  19. Jones, F.S.: 1958, J. Roy. Astron. Soc. Can. 52, 149. ADSGoogle Scholar
  20. Klimchuk, J.A.: 2001, In: Song, P., Singer, H., Siscoe, G. (eds.) Space Weather, Geophys. Monogr. Ser. 125, AGU, Washington, 143. CrossRefGoogle Scholar
  21. Low, B.C.: 1996, Solar Phys. 167, 217. ADSCrossRefGoogle Scholar
  22. Low, B.C.: 1999a, In: Habbal, S.R., Esser, R., Hollweg, J.V., Isenberg, P.A. (eds.) Solar Wind Nine, AIP Conf. Proc. 471, 109. Google Scholar
  23. Low, B.C.: 1999b, In: Brown, M.R., Canfield, R.C., Pevtsov, A.A. (eds.) Magnetic Helicity in Space and Laboratory Plasmas, Geophys. Monogr. Ser. 111, AGU, Washington, 25. CrossRefGoogle Scholar
  24. Low, B.C.: 2001a, J. Geophys. Res. 106, 25141. ADSCrossRefGoogle Scholar
  25. Low, B.C., Fong, B., Fan, Y.: 2003, Astrophys. J. 594, 1060. ADSCrossRefGoogle Scholar
  26. Menzel, D.H., Evans, J.W.: 1953, Accad. Naz. Lincei 11, 119. Google Scholar
  27. Menzel, D.H., Jones, F.S.: 1962, J. Roy. Astron. Soc. Can. 53, 193. ADSGoogle Scholar
  28. Moon, Y.J., Choe, G.S., Wang, H., Park, Y.D., Gopalswamy, N., Yang, G., Yashiro, S.: 2002, Astrophys. J. 581, 694. ADSCrossRefGoogle Scholar
  29. Munro, R.H., Gosling, J.T., Hildner, E., MacQueen, R.M., Poland, A.I., Ross, C.L.: 1979, Solar Phys. 61, 201. ADSCrossRefGoogle Scholar
  30. Pick, M., Lathuillere, C., Lilensten, J.: 2001, ESA Space Weather Programme Feasibility Studies, Alcatel-LPCE Consortium. Google Scholar
  31. Pojoga, S., Huang, T.S.: 2003, Adv. Space Res. 32, 2641. ADSGoogle Scholar
  32. Poland, A.I., Howard, R.A., Koomen, M.J., Michels, D.J., Sheeley, N.R.: 1981, Solar Phys. 69, 169. ADSCrossRefGoogle Scholar
  33. Qahwaji, R., Colak, T.: 2007, Solar Phys. 241, 195. ADSCrossRefGoogle Scholar
  34. Qahwaji, R., Al-Omari, M., Colak, T., Ipson, S.: 2008a, In: Villanueva, J.J. (ed.) IASTED International Conference on Visualization, Imaging and Image Processing (VIIP 2008), ACTA Press, Calgary, 808. Google Scholar
  35. Qahwaji, R., Al-Omari, M., Colak, T., Ipson, S.: 2008b, In: Mahasneh, J. (ed.) Mosharaka International Conference on Communications, Computers and Applications (MIC-CCA 2008), Mosharaka for Researches and Studies, 37. Google Scholar
  36. Qahwaji, R., Colak, T., Al-Omari, M., Ipson, S.: 2008c, Solar Phys. 248, 471. ADSCrossRefGoogle Scholar
  37. Rüping, S.: 2000, MySVM Manual, Lehrstuhl Informatik 8, University of Dortmund. Google Scholar
  38. Schapire, R.E., Singer, Y.: 1999, Mach. Learn. 37, 297. zbMATHCrossRefGoogle Scholar
  39. Sheeley, N.R., Walters, J.H., Wang, Y.-M., Howard, R.A.: 1999, J. Geophys. Res. 104, 24739. ADSCrossRefGoogle Scholar
  40. Srivastava, N., Gonzalez, W.D., Sawant, H.S.: 1997, Adv. Space Res. 20, 2355. ADSCrossRefGoogle Scholar
  41. St .Cyr, O.C., Webb, D.F.: 1991, Solar Phys. 136, 379. ADSCrossRefGoogle Scholar
  42. St. Cyr, O.C., Burkepile, J.T., Hundhausen, A.J., Lecinski, A.R.: 1999, J. Geophys. Res. 104, 12493. ADSCrossRefGoogle Scholar
  43. Subramanian, P., Dere, K.P.: 2001, Astrophys. J. 561, 372. ADSCrossRefGoogle Scholar
  44. Vezhnevets, A., Vezhnevets, V.: 2005, Modest Adaboost – Teaching Adaboost to Generalize Better, Graphicon. Google Scholar
  45. Webb, D.F.: 2000, J. Atmos. Solar-Terr. Phys. 62, 1415. ADSCrossRefGoogle Scholar
  46. Webb, D.F., Hundhausen, A.J.: 1987, Solar Phys. 108, 383. ADSCrossRefGoogle Scholar
  47. Webb, D.F., Cliver, E.W., Gopalswamy, N., Hudson, H.S., St. Cyr, O.C.: 1998, Geophys. Res. Lett. 25, 2469. ADSCrossRefGoogle Scholar
  48. Wilson, R.M., Hildner, E.: 1984, Solar Phys. 91, 169. ADSCrossRefGoogle Scholar
  49. Yang, G., Wang, H.: 2002, In: Wang, H., Xu, R. (eds.) Solar-Terrestrial Magnetic Activity and Space Environment, COSPAR Colloq. 14, 113. Google Scholar
  50. Yashiro, S., Gopalswamy, N., Michalek, G., St. Cyr, O.C., Plunkett, S.P., Rich, N.B., Howard, R.A.: 2004, J. Geophys. Res. 109, A07105. CrossRefGoogle Scholar
  51. Yashiro, S., Gopalswamy, N., Akiyama, S., Michalek, G., Howard, R.A.: 2005, J. Geophys. Res. 110, A12S05. ADSCrossRefGoogle Scholar
  52. Yashiro, S., Gopalswamy, N., Akiyama, S., Howard, R.A.: 2006, 36th COSPAR Scientific Assembly, 1778. Google Scholar
  53. Zhang, M., Low, B.C.: 2004, Astrophys. J. 600, 1043. ADSCrossRefGoogle Scholar
  54. Zhou, G., Wang, J., Cao, Z.: 2003, Astron. Astrophys. 397, 1057. ADSCrossRefGoogle Scholar
  55. Zirin, H.: 1966, The Solar Atmosphere, Waltham, Blaisdell-Ginn, 297. Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.School of Computing, Informatics & MediaUniversity of BradfordBradfordUK

Personalised recommendations