دورية أكاديمية
Echo state network model for analyzing solar-wind effects on the AU and AL indices
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 |
تدمد: | 09927689 14320576 |
---|---|
DOI: | 10.5194/angeo-40-11-2022 |