Application of Kernel Based Machine Learning to the Inversion Problem of Photospheric Magnetic Fields
文献类型：期刊论文
| 作者 | Teng, Fei
|
| 刊名 | SOLAR PHYSICS
 |
| 出版日期 | 2015-10-01 |
| 卷号 | 290期号:10页码:2693-2708 |
| 关键词 | Statistical machine learning Support vector machine regression Inversion of photospheric magnetic field Solar spectropolarimeter |
| 英文摘要 | For the purpose of fast methods for handling huge amounts of data coming from future solar spectropolarimeters, the statistical machine-learning techniques based on Mercer's kernel were applied to the inversion of the photospheric magnetic fields from polarimetric data. In particular, the Regularized Neural Network and the Support Vector Machine were tested for the data from the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory. |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000365220000004 |
| 源URL | [http://ir.bao.ac.cn/handle/114a11/5528]  |
| 专题 | 国家天文台_太阳物理研究部 |
| 作者单位 | Chinese Acad Sci, Natl Astron Observ, Key Lab Solar Act, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Teng, Fei. Application of Kernel Based Machine Learning to the Inversion Problem of Photospheric Magnetic Fields[J]. SOLAR PHYSICS,2015,290(10):2693-2708. |
| APA | Teng, Fei.(2015).Application of Kernel Based Machine Learning to the Inversion Problem of Photospheric Magnetic Fields.SOLAR PHYSICS,290(10),2693-2708. |
| MLA | Teng, Fei."Application of Kernel Based Machine Learning to the Inversion Problem of Photospheric Magnetic Fields".SOLAR PHYSICS 290.10(2015):2693-2708. |
入库方式： OAI收割
来源：国家天文台
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