Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Park, Wooyeon"'
Obtaining a sufficient forecast lead time for local precipitation is essential in preventing hazardous weather events. Global warming-induced climate change increases the challenge of accurately predicting severe precipitation events, such as heavy r
Externí odkaz:
http://arxiv.org/abs/2310.20187
Autor:
Park Wooyeon, Lee Jaejin, Kim Kyung-Chan, Lee JongKil, Park Keunchan, Miyashita Yukinaga, Sohn Jongdae, Park Jaeheung, Kwak Young-Sil, Hwang Junga, Frias Alexander, Kim Jiyoung, Yi Yu
Publikováno v:
Journal of Space Weather and Space Climate, Vol 11, p 38 (2021)
In this paper, an operational Dst index prediction model is developed by combining empirical and Artificial Neural Network (ANN) models. ANN algorithms are widely used to predict space weather conditions. While they require a large amount of data for
Externí odkaz:
https://doaj.org/article/06584567789743f98be81ec67584aecf
Autor:
Jongdae Sohn, Yukinaga Miyashita, Young-Sil Kwak, Jaeheung Park, Jaejin Lee, Jongkil Lee, Keunchan Park, Ji-Young Kim, Alexander Frias, Junga Hwang, Park Wooyeon, Yu Yi, Kyung-Chan Kim
Publikováno v:
Journal of Space Weather and Space Climate, Vol 11, p 38 (2021)
In this paper, an operational Dst index prediction model is developed by combining empirical and Artificial Neural Network (ANN) models. ANN algorithms are widely used to predict space weather conditions. While they require a large amount of data for