Support vector machine combined with K-nearest neighbors for solar flare forecasting
文献类型：期刊论文
| 作者 | Li, Rong; Wang, Hua-Ning ; He, Han; Cui, Yan-Mei; Du, Zhan-Le
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| 刊名 | CHINESE JOURNAL OF ASTRONOMY AND ASTROPHYSICS
 |
| 出版日期 | 2007 |
| 卷号 | 7期号:3页码:441-447 |
| 关键词 | sun : flare sun : sunspot sun : activity sun : magnetic fields |
| 英文摘要 | A method combining the support vector machine (SVM) the K-Nearest Neighbors (KNN), labelled the SVM-KNN method, is used to construct a solar flare forecasting model. Based on a proven relationship between SVM and KNN, the SVM-KNN method improves the SVM algorithm of classification by taking advantage of the KNN algorithm according to the distribution of test samples in a feature space. In our flare forecast study, sunspots and 10 cm radio flux data observed during Solar Cycle 23 are taken as predictors, and whether an M class flare will occur for each active region within two days will be predicted. The SVM-KNN method is compared with the SVM and Neural networks-based method. The test results indicate that the rate of correct predictions from the SVM-KNN method is higher than that from the other two methods. This method shows promise as a practicable future forecasting model. |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000247553300015 |
| 源URL | [http://ir.bao.ac.cn/handle/114a11/7289]  |
| 专题 | 国家天文台_太阳物理研究部 |
| 作者单位 | Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Rong,Wang, Hua-Ning,He, Han,et al. Support vector machine combined with K-nearest neighbors for solar flare forecasting[J]. CHINESE JOURNAL OF ASTRONOMY AND ASTROPHYSICS,2007,7(3):441-447. |
| APA | Li, Rong,Wang, Hua-Ning,He, Han,Cui, Yan-Mei,&Du, Zhan-Le.(2007).Support vector machine combined with K-nearest neighbors for solar flare forecasting.CHINESE JOURNAL OF ASTRONOMY AND ASTROPHYSICS,7(3),441-447. |
| MLA | Li, Rong,et al."Support vector machine combined with K-nearest neighbors for solar flare forecasting".CHINESE JOURNAL OF ASTRONOMY AND ASTROPHYSICS 7.3(2007):441-447. |
入库方式： OAI收割
来源：国家天文台
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