APPLICATION OF SUPPORT VECTOR MACHINE TO THE PREDICTION OF GEO-EFFECTIVE HALO CMES |
Choi, Seong-Hwan
(Korea Astronomy and Space Science Institute)
Moon, Yong-Jae (Department of Astronomy and Space Science, Kyung Hee University) Vien, Ngo Anh (Institute for Artificial Intelligence, Ravensburg-Weingarten University of Applied Sciences) Park, Young-Deuk (Korea Astronomy and Space Science Institute) |
1 | Yuan, Y., Shih, F. Y., Jing, J., &Wang, H. 2010, Auto- mated Flare Forecasting using a Statistical Learning Technique, Res. Astron. Astrophys., 10, 785 DOI ScienceOn |
2 | Zhang, J., Richardson, I. G., Webb, D. F., Gopal- swamy, N., Huttunen, E., Kasper, J. C., Nitta, N. V., Poomvises, W., Thompson, B. J., Wu, C.-C., Yashiro, S., & Zhukov, A. N. Solar and Interplane- tary Sources of Major Geomagnetic Storms (Dst -100 nT) during 1996-2005, JGRA, 112, A10 |
3 | Liu, D. D., Huang, C., Lu, J. Y., & Wang, J. S. 2011, The Hourly Average Solar Wind Velocity Prediction Based on Support Vector Regression Method, MNRAS, 413, 2877 DOI ScienceOn |
4 | Qahwaji, R., Colak, T., Al-Omari, M., & Ipson, S. 2008, Automated Prediction of CMEs Using Ma- chine Learning of CME-Flare Associations, Solar Physics, 248, 471 DOI ScienceOn |
5 | Martens, P. C. H., Attrill, G. D. R., Davey, A. R., Engell, A., Farid, S., Grigis, P. C., Kasper, J., Kor- reck, K., Saar, S. H., Savcheva, A., Su, Y., Testa, P., Wills-Davey, M., Bernasconi, P. N., Raouafi, N.-E., Delouille, V. A., Hochedez, J. F., Cirtain, J.W., De- forest, C. E., Angryk, R. A., de Moortel, I., Wiegel- mann, T., Georgoulis, M. K., McAteer, R. T. J., & Timmons, R. P. 2009, Computer Vision for the Solar Dynamics Observatory (SDO), Solar Physics, tmp 144 |
6 | Moon, Y.-J., Cho, K.-S., Chae, J., Choe, G. S., Kim, Y.-H., Bong, S.-C., & Park, Y.-D. New Extrapola- tion Method for Coronal Mass Ejection Onset Time Estimation, JGR, 110, A7 |
7 | Qahwaji, R., & Colak, T. 2007, Automated Short- Solar Flare Prediction Using Machine Learning and Sunspot Associations, Solar Physics, 241, 195 DOI ScienceOn |
8 | Qu, M., Shih, F. Y., Jing, J., & Wang, H. 2003, Auto- mated Solar Flare Detection Using MLP, RBF, and SVM, Solar Physics, 217, 157 DOI ScienceOn |
9 | Qu, M., Shin, F. Y., Jing, J., & Wang, H. 2005, Au- tomatic Solar Filament Detection Using Image Pro- cessing Techniques, Solar Physics, 228, 119 DOI ScienceOn |
10 | Srivastava, N. K., & Venkatakrishnan, P. 2004, Solar and Interplanetary Sources of Major Geomagnetic Storms during 1996-2002, JGR, 109, A10 |
11 | Wang, Y.M., Ye, P. Z.,Wang, S., Zhou, G. P., &Wang, J. X. 2002, A Statistical Study on the Geoeffective- ness of Earth-Directed Coronal Mass Ejections from March 1997 to December 2000, JGR, 107, A11 |
12 | Webb, D. F. 2002, CMEs and the Solar Cycle Varia- tion in Their Geoeffectiveness, ISBN 92-9092-818-2, 2002, 409 |
13 | Yu, D., Huang, X., Wang, H., & Cui, Y. 2009, Short- Term Solar Flare Prediction Using a Sequential Supervised Learning Method, Solar Physics, 255, 91 DOI ScienceOn |
14 | Gopalswamy, N., Lara, A., Yashiro, S., Kaiser, M. L., & Howard, R. A. Predicting the 1-AU Arrival Times of Coronal Mass Ejections, JGR, 106, A12, 29207 |
15 | Colak, T., & Qahwaji, R. 2009, Automated Solar Ac- tivity Prediction: A Hybrid Computer Platform Us- ing Machine Learning and Solar Imaging for Auto- mated Prediction of Solar Flares, Space Weather, Vol. 7, S06001, 12PP |
16 | Cortes, C., & Vapnik, V. 1995, Support-Vector Networks, Machine Learning, 20 |
17 | Gavrishchaka, V. V., & Ganguli, S. B. 2001, Support Vector Machine as an Efficient Tool for High-Dimensional Data Processing: Application to Substorm Forecasting, JGR, 106, 29911 DOI |
18 | Gopalswamy, N., Yashiro, S., & Akiyama, S. Geoeffec- tiveness of Halo Coronal Mass Ejections, JGR, 112, A6 |
19 | He, H., Wang, H., Du, z., Li, R., Chui, Y., Zhang, L., & He, Y. 2008, Solar Activity Prediction Studies and Services in NAOC, Advances in Space Research, 42, 1450 DOI ScienceOn |
20 | Henwood, R., Chapman, S. C., & Willis, D. M. 2010, Increasing Lifetime of Recurrent Sunspot Groups Within the Greenwich Photoheliographic Results, Solar Physics, 262, 299 DOI ScienceOn |
21 | Kim, R.-S., Cho, K.-S., Moon, Y.-J., Kim, Y.-H., Yi, Y., Dryer, M., Bong, S.-C., & Park, Y.-D. 2005, Forecast Evaluation of the Coronal Mass Ejection (CME), Geoeffectiveness Using Halo CMEs from 1997 to 2003, JGR, 110, A11104 DOI |
22 | Kim, R.-S., Cho, K.-S., Kim, K.-H., Park, Y.-D., Moon, Y.-J., Yi, Y., Lee, J., Wang, H., Song, H., & Dryer, M. 2008, CME Earthward Direction as an Important Geoeffectiveness Indicator, ApJ, 677, 1378 DOI |
23 | Labrosse, N., Dalla, S., & Marshall, S. 2010, Auto- mated Detection of Limb Prominences in 304 A EUV Images, Solar Physics, 262, 449 DOI ScienceOn |
24 | Boser, B. E., Guyon, I. M., & Vapnik, V. N. 1992, 5th Annual ACM Workshop on COLT, pages 144152, Pittsburgh, PA, A training algorithm for optimal margin classifiers. In D. Haussler, editor, ACM Press |
25 | Li, R., Wang, H.-N., He, H., Cui, Y.-M., & Du, Z.-L. 2007, Support Vector Machine Combined with K- Nearest Neighbors for Solar Flare Forecasting, Chin. J. Astron. Astrophys., Vol. 7, No. 3, 441 DOI ScienceOn |
26 | Al-Omari, M., Qahwaji, R., Colak, T., & Ipson, S. 2010, Machine Learning-Based Investigation of the Associations between CMEs and Filaments, Solar Physics, 262, 511 DOI ScienceOn |
27 | Attrill, G. D. R., &Wills-Davey, M. J. 2010, Automatic Detection and Extraction of Coronal Dimmings from SDO/AIA Data, Solar Physics, 262, 461 DOI ScienceOn |
28 | Chen, C., Wu, Z. S., Xu, Z. W., Sun, S. J., Ding, Z. H., & Ban, P. P. 2010, Forecasting the Local Ionospheric f0F2 Parameter 1 Hour ahead during Disturbed Ge- omagnetic Conditions, JGR, 115, A11315 DOI |
29 | Chang, C.-C., & Lin, C.-J. 2001, LIBSVM : A Library for Support Vector Machines, http://www.csie.ntu.edu.tw/ cjlin/libsvm |