Volume 39 Issue 3
May  2019
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YE Yudong, FENG Xueshang. Study on Geoeffectiveness of Interplanetary Coronal Mass Ejections by Support Vector Machine ormalsize[J]. Journal of Space Science, 2019, 39(3): 295-302. doi: 10.11728/cjss2019.03.295
Citation: YE Yudong, FENG Xueshang. Study on Geoeffectiveness of Interplanetary Coronal Mass Ejections by Support Vector Machine ormalsize[J]. Journal of Space Science, 2019, 39(3): 295-302. doi: 10.11728/cjss2019.03.295

Study on Geoeffectiveness of Interplanetary Coronal Mass Ejections by Support Vector Machine ormalsize

doi: 10.11728/cjss2019.03.295
  • Received Date: 2018-06-05
  • Rev Recd Date: 2019-01-31
  • Publish Date: 2019-05-15
  • As arriving at the Earth, Interplanetary Coronal Mass Ejections (ICME) will interact with the Earth's magnetosphere and cause geomagnetic storms. The ICME event set is obtained by Richardson and Cane's Near Earth ICME list, and the input features are extracted based on interplanetary solar wind and magnetic data during ICME disturbance. A total of 483 ICME events from 1996 to 2006 are chosen in this study. 13 magnetic and kinetic features are finally selected for the training of the machine learning model. Rank of each feature's Fisher score indicates that the duration of the south-directed interplanetary magnetic field that is larger than 10nT and the increase of solar wind speed at the upstream shock or wave disturbance is closely related to the geoeffectiveness of ICME events, which is consistent with those former statistical results. The trained Radial Basis Function Support Vector Machine (RBF-SVM) can determine whether an ICME event could trigger moderate or stronger geomagnetic storms (Dst ≤ -50nT) effectively with an accuracy of 0.78±0.08. The results show that RBF-SVM can be used as a powerful tool in further analysis, and the better prediction of the geoeffectiveness of ICME will be obtained.


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  • [1]
    ZURBUCHEN T H, RICHARDSON I G. In-situ solar wind and magnetic field signatures of interplanetary coronal mass ejections[J]. Space Sci. Rev., 2006, 123(1/2/3):31-43
    LAKHINA G S, TSURUTANI B T. Geomagnetic storms:historical perspective to modern view[J]. Geosci. Lett., 2016, 3(1):5
    GONZALEZ W D, JOSELYN J A, KAMIDE Y, et al. What is a geomagnetic storm[J]. J. Geophys. Res., 1994, 99:5771-5792
    WU J G, LUNDSTEDT H. Geomagnetic storm predictions from solar wind data with the use of dynamic neural networks[J]. J. Geophys. Res.:Space Phys., 1997, 102(A7):14255-14268
    BALA R, REIFF P. Improvements in short-term forecasting of geomagnetic activity[J]. Space Weather, 2012, 10(6).DOI: 10.1029/2012SW000779.
    WATANABE S, SAGAWA E, OHTAKA K, et al. Prediction of the Dst index from solar wind parameters by a neural network method[J]. Earth Planets Space, 2014, 54(12):1263-1275
    WANG Y M, YE P Z, WANG S, et al. A statistical study on the geoeffectiveness of Earth-directed coronal mass ejections from March 1997 to December 2000[J]. J. Geophys. Res., 2002, 107(A11).DOI: 10.1029/2002JA009244.
    GOPALSWAMY N, YASHIRO S, XIE H, et al. Properties and geoeffectiveness of magnetic clouds during solar cycles 23 and 24[J]. J. Geophys. Res.:Space Phys., 2015, 120(11):9221-9245
    LAWRANCE M B, SHANMUGARAJU A, MOON Y J, et al. Relationships between interplanetary coronal mass ejection characteristics and geoeffectiveness in the rising phase of solar cycles 23 and 24[J]. Sol. Phys., 2016, 291(5):1547-1560
    CANE H V, RICHARDSON I G. Interplanetary coronal mass ejections in the near-Earth solar wind during 1996-2002[J]. J. Geophys. Res., 2003, 108(A4).DOI:10. 1029/2002JA009817.
    RICHARDSON I G, CANE H V. Near-earth interplanetary coronal mass ejections during solar cycle 23(1996-2009):catalog and summary of properties[J]. Sol. Phys., 2010, 264(1):189-237
    MATHEWS G J, TOWHEED S S. NSSDC OMNIWeb:The first space physics WWW-based data browsing and retrieval system[J]. Comp. Networks ISDN Syst., 1995, 27(6):801-808
    GU Q Q, LI Z H, HAN J W. Generalized Fisher Score for Feature Selection[C]//Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence, 2011:266-273
    PEDREGOSA F, VAROQUAUX G, GRAMFORT A, et al. Scikit-learn:machine learning in Python[J]. J. Mach. Learn. Res., 2011, 12:2825-2530
    CHI Yutian, SHEN Chenglong, WANG Yuming, et al. Statistical study of the interplanetary coronal mass ejections from 1995 to 2015[J]. Sol. Phys., 2016, 291(8):2419-2439
    WANG Yuming, YE Pinzhong, WANG Shui. An interplanetary origin of great geomagnetic storms:multiple magnetic clouds[J]. Chin. J. Geophys., 2004, 47(3):417-423
    TSURUTANI B T, GONZALEZ W D, TANG F, et al. Great magnetic storms[J]. Geophys. Res. Lett., 1992, 19(1):73-76
    BURTON R K, MCPHERRON R L, RUSSELL C T. An empirical relationship between interplanetary conditions and Dst[J]. J. Geophys. Res., 1975, 80(31):4204-4214
    VAPNIK V, GOLOWICH S E, SMOLA A J. Support vector method for function approximation, regression estimation and signal processing[C]//Proceedings of the Advances in Neural Information Processing Systems, 1997:281-287
    AMARI S, MURATA N, MULLER K R, et al. Asymptotic statistical theory of overtraining and cross-validation[J]. IEEE Trans. Neural Netw., 1997, 8(5):985-996
    REFAEILZADEH P, TANG L, LIU H. Cross-validation[R]. Encyclopedia of Database System, US:Springer. DOI: 10.1007/978-0-387-39940-9_565
    KOHAVI R. A study of cross-validation and bootstrap for accuracy estimation and model selection[C]//Proceedings of the 14th International Joint Conference on Artificial Intelligence-Volume 2. Quebec:Morgan Kaufmann Publishers Inc, 1995:1137-1143
    FLUECK J. A study of some measures of forecast verification[C]//Proceedings of the Preprints, 10th Conference on Probability and Statistics in Atmospheric Sciences. Edmonton:Alberta, Am. Meteor. Soc., 1987:69-73
    SHEN Fang, WANG Yuming, SHEN Chenglong, et al. On the collision nature of two coronal mass ejections:a review[J]. Sol. Phys., 2017, 292(8):104
    SHEN Chenglong, CHI Yutian, WANG Yuming, et al. Statistical comparison of the ICME's geoeffectiveness of different types and different solar phases from 1995 to 2014[J]. J. Geophys. Res.:Space Phys., 2017, 122(6):5931-5948
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