Potential of Regional Ionosphere Prediction Using a Long Short‐Term Memory Deep‐Learning Algorithm Specialized for Geomagnetic Storm Period

Autor:	Young-Sil Kwak, Jeong-Heon Kim, Jongyeon Yun, Su-In Moon, Se-Heon Jeong, Yong Ha Kim
Rok vydání:	2021
Předmět:	Geomagnetic storm Atmospheric Science business.industry Deep learning Physics::Geophysics Long short term memory Earth's magnetic field Climatology QUIET Physics::Space Physics Artificial intelligence Ionosphere business Geology Period (music)
Zdroj:	Space Weather. 19
ISSN:	1542-7390
DOI:	10.1029/2021sw002741
Popis:	In our previous study (Moon et al., 2020), we developed a Long Short Term Memory (LSTM) deep-learning model for geomagnetic quiet days to perform effective long-term predictions for the regional io...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::57d4d69c719a7c5b9243027ce2309b07 https://doi.org/10.1029/2021sw002741 Zobrazit plný text záznamu Plný text