在整个太阳周期中对太阳风参数进行统计分析和预测
1College of Artificial Intelligence, Suzhou Chien-Shiung Institute of Technology, Suzhou, 215411, Jiangsu, China.
Scientific reports
|August 22, 2024
概括
这项研究分析了五个太阳周期的太阳风数据,发现与太阳黑子数量的相关性. 一个先进的LSTM+模型预测了太阳周期25,预测了它的峰值活动,并指出了潜在的双峰.
科学领域:
- 空间物理 空间物理
- 太阳物理 太阳物理
- 天体物理学 天体物理学
背景情况:
- 太阳风参数表现出与太阳周期相关的周期性.
- 了解太阳活动和太阳风之间的关系对于太空天气预报至关重要.
研究的目的:
- 在太阳周期20-24期间调查太阳风参数的统计性质.
- 分析太阳风参数和太阳黑子数 (SSN) 之间的相关性.
- 预测太阳周期25使用优化的长短期记忆 (LSTM+) 模型.
主要方法:
- 统计分析太阳风数据从太阳周期 20-24.
- 在平滑的27天平均太阳风参数和SSN之间进行了相关性分析.
- 优化LSTM+模型用于太阳周期25预测的应用.
主要成果:
- 确定了太阳风参数的周期性,与太阳周期保持一致.
- 在太阳风参数和SSN之间建立了显著的相关性.
- 预测太阳周期25峰值SSN发生在2024年10月27日左右±136天.
- 观察到太阳周期25活动的潜在双峰.
结论:
- 太阳风的特征受到太阳周期和太阳黑子活动的强烈影响.
- 该LSTM+模型显示了准确的太阳周期预测的前景.
- 太阳周期25预测的双峰,使预测其确切的大小和时间变得更加复杂.
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