文章基本信息

标题：Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network
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作者：Yi Yang ; Fang Shen ; Zicai Yang 等
期刊名称：Space Weather
印刷版ISSN：1542-7390
出版年度：2018
卷号：16
期号：9
页码：1227-1244
DOI：10.1029/2018SW001955
语种：English
出版社：American Geophysical Union
摘要：A hybrid intelligent source surface model applying the artificial neural network tactic for solar wind speed prediction is presented in this paper. The model is a hybrid system merging various observational and theoretical information as input. Different inputs are tested including individual parameters and their combinations in order to select an optimum. Then, the optimal model is implemented for prediction. The prediction is validated by both error analysis and event-based analysis from 2007 to 2016. The overall correlation coefficient is 0.74, and the root-mean-square error is 68 km/s. The probability for detecting a high-speed-event is 0.68, the positive predicted value is 0.73, and the threat score is 0.55.