NSSC OpenIR  > 空间科学部
Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network
Yang, Yi; Shen, Fang; Yang, Zicai; Feng, Xueshang
Department空间科学部
Source PublicationSPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
2018
Volume16Issue:9Pages:1227-1244
DOI10.1029/2018SW001955
ISSN1542-7390
Language英语
AbstractA 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.
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Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/6567
Collection空间科学部
Recommended Citation
GB/T 7714
Yang, Yi,Shen, Fang,Yang, Zicai,et al. Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,2018,16(9):1227-1244.
APA Yang, Yi,Shen, Fang,Yang, Zicai,&Feng, Xueshang.(2018).Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network.SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,16(9),1227-1244.
MLA Yang, Yi,et al."Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network".SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 16.9(2018):1227-1244.
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