| Predicting the Daily 10.7-cm Solar Radio Flux Using the Long Short-Term Memory Method | |
Zhang, Wanting1,2; Zhao, Xinhua1,3,4; Feng, Xueshang1; Liu, Cheng’ao5; Xiang NB(向南彬)6 ; Li, Zheng7; Lu, Wei1,2
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| 发表期刊 | UNIVERSE
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| 2022-01 | |
| 卷号 | 8期号:1 |
| DOI | 10.3390/universe8010030 |
| 产权排序 | 第6完成单位 |
| 收录类别 | SCI |
| 关键词 | solar radio flux time series forecast long short-term memory |
| 摘要 | As an important index of solar activity, the 10.7-cm solar radio flux (F-10.7) can indicate changes in the solar EUV radiation, which plays an important role in the relationship between the Sun and the Earth. Therefore, it is valuable to study and forecast F-10.7. In this study, the long short-term memory (LSTM) method in machine learning is used to predict the daily value of F-10.7. The F-10.7 series from 1947 to 2019 are used. Among them, the data during 1947-1995 are adopted as the training dataset, and the data during 1996-2019 (solar cycles 23 and 24) are adopted as the test dataset. The fourfold cross validation method is used to group the training set for multiple validations. We find that the root mean square error (RMSE) of the prediction results is only 6.20~6.35 sfu, and the correlation coefficient (R) is as high as 0.9883~0.9889. The overall prediction accuracy of the LSTM method is equivalent to those of the widely used autoregressive (AR) and backpropagation neural network (BP) models. Especially for 2-day and 3-day forecasts, the LSTM model is slightly better. All this demonstrates the potentiality of the LSTM method in the real-time forecasting of F-10.7 in future. |
| 资助项目 | N/A |
| 项目资助者 | N/A |
| 语种 | 英语 |
| 学科领域 | 天文学 ; 射电天文学 ; 射电天文方法 ; 太阳与太阳系 |
| 文章类型 | Article |
| 出版者 | MDPI |
| 出版地 | ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND |
| URL | 查看原文 |
| WOS记录号 | WOS:000757157500001 |
| WOS研究方向 | Astronomy & Astrophysics ; Physics |
| WOS类目 | Astronomy & Astrophysics ; Physics, Particles & Fields |
| 关键词[WOS] | CM ; F10.7 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 版本 | 出版稿 |
| 条目标识符 | http://ir.ynao.ac.cn/handle/114a53/24907 |
| 专题 | 抚仙湖太阳观测和研究基地 |
| 作者单位 | 1.State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China; 2.School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China; 3.Yading Space Weather Science Center, Daocheng 627750, China; 4.CAS Key Laboratory of Solar Activity, National Astronomical Observatories, Beijing 100101, China; 5.CAEIT, Beijing 100041, China; 6.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650011, China; 7.Institute of Space Weather, Nanjing University of Information Science & Technology, Nanjing 210044, China |
| 推荐引用方式 GB/T 7714 | Zhang, Wanting,Zhao, Xinhua,Feng, Xueshang,et al. Predicting the Daily 10.7-cm Solar Radio Flux Using the Long Short-Term Memory Method[J]. UNIVERSE,2022,8(1). |
| APA | Zhang, Wanting.,Zhao, Xinhua.,Feng, Xueshang.,Liu, Cheng’ao.,向南彬.,...&Lu, Wei.(2022).Predicting the Daily 10.7-cm Solar Radio Flux Using the Long Short-Term Memory Method.UNIVERSE,8(1). |
| MLA | Zhang, Wanting,et al."Predicting the Daily 10.7-cm Solar Radio Flux Using the Long Short-Term Memory Method".UNIVERSE 8.1(2022). |
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| Predicting the Daily（4975KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 | |
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