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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Bibliographic Details

Published in:	2015 IEEE 11th International Conference on e-Science pp. 284 - 287
Main Authors:	Tanaka, Takanori, Kitao, Daisuke, Sato, Yuka, Tanaka, Yoshimasa, Ikeda, Daisuke
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.08.2015
Subjects:	Accuracy Forecasting Kernel Supervised learning Support vector machines time series data Training data Wind forecasting
Online Access:	Get full text
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