Predicting the 25th and 26th solar cycles using the long short-term memory method | |
Liu, Xiaohuan2,3; Zeng, Shuguang2,3; Deng LH(邓林华)1; Zeng, Xiangyun2,3; Zheng, Sheng2,3 | |
刊名 | PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN |
2023-05 | |
关键词 | Method: LSTM Sun: activity Sun: solar cycle predict Sun: sunspots |
ISSN号 | 0004-6264 |
DOI | 10.1093/pasj/psad029 |
产权排序 | 第3完成单位 |
文献子类 | Article; Early Access |
英文摘要 | Solar activities directly or indirectly affect space missions, geophysical environment, space climate, and human activities. We used the long short-term memory (LSTM) deep learning method to predict the amplitude and peak time of solar cycles (SCs) 25 and 26 by using the monthly relative sunspot number data taken from the National Astronomical Observatory of Japan (NAOJ). The dataset is divided into eight schemes of two to nine slices for training, showing that the five-slice LSTM model with root mean square error of 11.38 is the optimal model. According to the prediction, SC 25 will be about 21% stronger than SC 24, with a peak of 135.2 occurring in 2024 April. SC 26 will be similar to SC 25 and reach its peak of 135.0 in 2035 January. Our analysis results indicate that the sunspot data from NAOJ is highly credible and comparable. |
学科主题 | 天文学 ; 太阳与太阳系 ; 太阳物理学 |
URL标识 | 查看原文 |
出版地 | GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND |
WOS关键词 | NEURAL-NETWORK ; AMPLITUDE ; LSTM |
WOS研究方向 | Astronomy & Astrophysics |
语种 | 英语 |
出版者 | OXFORD UNIV PRESS |
WOS记录号 | WOS:000981345800001 |
资助机构 | Yunnan Key Laboratory of Solar Physics and Space Science[YNSPCC202208] ; National Natural Science Foundation of China[U2031202, 12203029, 11873089] ; CAS Light in Western China Program, Yunnan Fundamental Research Projects[202301AV070007] ; Yunnan Province XingDian Talent Support Program |
内容类型 | 期刊论文 |
版本 | 出版稿 |
源URL | [http://ir.ynao.ac.cn/handle/114a53/25918] |
专题 | 云南天文台_抚仙湖太阳观测站 |
通讯作者 | Deng LH(邓林华); Zeng, Xiangyun; Zheng, Sheng |
作者单位 | 1.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, People’s Republic of China 2.College of Science, China Three Gorges University, Yichang 443000, People’s Republic of China; 3.Center for Astronomy and Space Sciences, China Three Gorges University, Yichang 443000, People’s Republic of China; |
推荐引用方式 GB/T 7714 | Liu, Xiaohuan,Zeng, Shuguang,Deng LH,et al. Predicting the 25th and 26th solar cycles using the long short-term memory method[J]. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN,2023. |
APA | Liu, Xiaohuan,Zeng, Shuguang,Deng LH,Zeng, Xiangyun,&Zheng, Sheng.(2023).Predicting the 25th and 26th solar cycles using the long short-term memory method.PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN. |
MLA | Liu, Xiaohuan,et al."Predicting the 25th and 26th solar cycles using the long short-term memory method".PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN (2023). |
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