دورية أكاديمية
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Echo state network model for analyzing solar-wind effects on the AU and AL indices

التفاصيل البيبلوغرافية
العنوان: Echo state network model for analyzing solar-wind effects on the AU and AL indices
المؤلفون: S. Nakano, R. Kataoka
المصدر: Annales Geophysicae, Vol 40, Pp 11-22 (2022)
بيانات النشر: Copernicus Publications, 2022.
سنة النشر: 2022
المجموعة: LCC:Science
LCC:Physics
LCC:Geophysics. Cosmic physics
مصطلحات موضوعية: Science, Physics, QC1-999, Geophysics. Cosmic physics, QC801-809
الوصف: The properties of the auroral electrojets are examined on the basis of a trained machine-learning model. The relationships between solar-wind parameters and the AU and AL indices are modeled with an echo state network (ESN), a kind of recurrent neural network. We can consider this trained ESN model to represent nonlinear effects of the solar-wind inputs on the auroral electrojets. To identify the properties of auroral electrojets, we obtain various synthetic AU and AL data by using various artificial inputs with the trained ESN. The analyses of various synthetic data show that the AU and AL indices are mainly controlled by the solar-wind speed in addition to Bz of the interplanetary magnetic field (IMF) as suggested by the literature. The results also indicate that the solar-wind density effect is emphasized when solar-wind speed is high and when IMF Bz is near zero. This suggests some nonlinear effects of the solar-wind density.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 0992-7689
1432-0576
Relation: https://angeo.copernicus.org/articles/40/11/2022/angeo-40-11-2022.pdf; https://doaj.org/toc/0992-7689; https://doaj.org/toc/1432-0576
DOI: 10.5194/angeo-40-11-2022
URL الوصول: https://doaj.org/article/54ad739c36f04afebe4864eabcf88f63
رقم الأكسشن: edsdoj.54ad739c36f04afebe4864eabcf88f63
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:09927689
14320576
DOI:10.5194/angeo-40-11-2022