Forecasting Auroral Substorms from Observed Data with a Supervised Learning Algorithm

Auroras are beautiful phenomena and attract many people. However, its physical model still remains a subject of dispute because it is caused by the interaction of diverse areas, such as solar wind, magnetosphere, and ionosphere, and it is difficult to simultaneously obtain data in such wide areas. T...

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Vydané v:	2015 IEEE 11th International Conference on e-Science s. 284 - 287
Hlavní autori:	Tanaka, Takanori, Kitao, Daisuke, Sato, Yuka, Tanaka, Yoshimasa, Ikeda, Daisuke
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.08.2015
Predmet:	Accuracy Forecasting Kernel Supervised learning Support vector machines time series data Training data Wind forecasting
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