Statistical analysis and forecasting of solar wind parameters across solar cycles

被引:3
作者
He, Mu [1 ]
Zhu, Hongbing [2 ]
机构
[1] Suzhou Chien Shiung Inst Technol, Coll Artificial Intelligence, Suzhou 215411, Jiangsu, Peoples R China
[2] Avant Courier Lab, Hiroshima, Japan
基金
美国国家航空航天局;
关键词
Solar cycle; Solar wind; Plasma Beta; LSTM plus; SUN;
D O I
10.1038/s41598-024-70564-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This study investigated the statistical properties of solar wind parameters spanning Solar Cycles 20-24, elucidating periodicities that closely aligned with the solar cycle. Significantly, correlations between the smoothed 27-day average value of solar wind parameters and sunspot numbers (SSN) were discerned, shedding light on the intricate interplay between solar activity and solar wind characteristics. Furthermore, the study employed an optimized Long Short-Term Memory (LSTM+) model for forecasting Solar Cycle 25, demonstrating promising predictive capabilities. The analysis predicted the occurrence time of the peak value of SSN in Solar Cycle 25 to be on 27 October 2024 +/- 136 days, based on the average relationship with the occurrence time of the trough of Plasma Beta. Notably, observations revealed a double peak in SC-25's solar activity, introducing uncertainty regarding the relative magnitude of each peak.
引用
收藏
页数:8
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