LSTM 和 OKSM 对 2023 年发生 M 级太阳耀斑期间电离层 TEC 的预测

IF 1.8 4区 物理与天体物理 Q3 ASTRONOMY & ASTROPHYSICS
R. Mukesh, Sarat C. Dass, M. Vijay, S. Kiruthiga, Vijanth Sagayam
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引用次数: 0

摘要

空间天气预报的进步对于了解和减轻太阳活动对地球电离层的影响至关重要。这项研究的重点是预测 2023 年 M 级太阳耀斑事件期间的总电子含量(TEC)。TEC 是卫星通信和导航的重要参数,因此必须进行准确预测。研究采用了两种预测模型,即长短期记忆(LSTM)神经网络和基于普通克里金(OKSM)的代用模型。LSTM 以捕捉时间相关性而著称,而 OKSM 则是一种捕捉空间自相关性的地理统计插值技术。研究利用海德拉巴(HYDE)全球定位系统站的 TEC 测量数据以及太阳和地磁参数进行模型训练和评估。使用均方根误差(RMSE)、归一化均方根误差(RMSE)、相关系数(CC)和对称平均绝对百分比误差(sMAPE)测量了两个模型在不同太阳耀斑日期的性能指标。研究对结果进行了解释,强调了每个模型的优势和局限性。值得注意的发现包括 LSTM 在捕捉时间变化方面的能力和 OKSM 独特的空间视角。研究分别分析了不同的太阳耀斑强度,证明了模型对不同空间天气条件的适应性。在 M 4.65 SF 事件中,OKSM 模型的平均性能指标为均方根误差 5.61、归一化均方根误差 0.14、相关系数 0.9813 和对称平均绝对百分比误差 14.90。同样,对于 LSTM,相应的平均值分别为 10.03、0.24、0.9313 和 28.64。这项研究为 LSTM 和 OKSM 在太阳耀斑事件期间对 TEC 的预测能力提供了宝贵的见解。这些成果有助于理解机器学习和地质统计技术在空间天气预测中的适用性。随着社会对易受空间天气影响的技术的依赖与日俱增,这项研究对于加强空间天气预报和确保地球上关键技术基础设施的稳健性至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prediction of ionospheric TEC by LSTM and OKSM during M class solar flares occurred during the year 2023

Prediction of ionospheric TEC by LSTM and OKSM during M class solar flares occurred during the year 2023

Advancements in space weather forecasting have become crucial for understanding and mitigating the impacts of solar activity on Earth’s ionosphere. This research focuses on the prediction of Total Electron Content (TEC) during M-class solar flare events in 2023. TEC is a vital parameter for satellite communications and navigation, making accurate forecasting imperative. Two prediction models, Long Short-Term Memory (LSTM) neural networks and Surrogate Models based on Ordinary Kriging (OKSM), are employed. LSTM, known for capturing temporal dependencies, is contrasted with OKSM, a geostatistical interpolation technique capturing spatial autocorrelation. The study utilizes TEC measurements from the Hyderabad (HYDE) GPS station for model training and evaluation along with solar and geomagnetic parameters. The performance metrics for both models across various solar flare dates are measured using Root Mean Square Error (RMSE), Normalized RMSE, Correlation Coefficient (CC), and Symmetric Mean Absolute Percentage Error(sMAPE). The research interprets the results, highlighting the strengths and limitations of each model. Notable findings include LSTM’s proficiency in capturing temporal variations and OKSM’s unique spatial perspective. Different solar flare intensities are analyzed separately, demonstrating the model’s adaptability to varying space weather conditions. The average performance metrics during M 4.65 SF events for the OKSM model, in terms of Root Mean Square Error is 5.61, Normalized RMSE is 0.14, Correlation Coefficient is 0.9813, and Symmetric Mean Absolute Percentage Error is 14.90. Similarly, for LSTM, the corresponding averages are 10.03, 0.24, 0.9313, and 28.64. The research contributes valuable insights into the predictive capabilities of LSTM and OKSM for TEC during solar flare events. The outcomes aid in understanding the applicability of machine learning and geostatistical techniques in space weather prediction. As society’s reliance on technology susceptible to space weather effects grows, this research is pivotal for enhancing space weather forecasts and ensuring the robustness of critical technological infrastructure on Earth.

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来源期刊
Astrophysics and Space Science
Astrophysics and Space Science 地学天文-天文与天体物理
CiteScore
3.40
自引率
5.30%
发文量
106
审稿时长
2-4 weeks
期刊介绍: Astrophysics and Space Science publishes original contributions and invited reviews covering the entire range of astronomy, astrophysics, astrophysical cosmology, planetary and space science and the astrophysical aspects of astrobiology. This includes both observational and theoretical research, the techniques of astronomical instrumentation and data analysis and astronomical space instrumentation. We particularly welcome papers in the general fields of high-energy astrophysics, astrophysical and astrochemical studies of the interstellar medium including star formation, planetary astrophysics, the formation and evolution of galaxies and the evolution of large scale structure in the Universe. Papers in mathematical physics or in general relativity which do not establish clear astrophysical applications will no longer be considered. The journal also publishes topically selected special issues in research fields of particular scientific interest. These consist of both invited reviews and original research papers. Conference proceedings will not be considered. All papers published in the journal are subject to thorough and strict peer-reviewing. Astrophysics and Space Science features short publication times after acceptance and colour printing free of charge.
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