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Solar Wind Speed Prediction With Two-Dimensional Attention Mechanism
Sun, Yanru1; Xie, Zongxia1; Chen, Yanhong2; Huang, Xin3; Hu, Qinghua1
2021-07-01
Source PublicationSPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
Volume19Issue:7Pages:15
AbstractAs more and more high-technical systems are exposed to the space environment, extreme space weather becomes a great threat to human society. In the solar system, space weather is influenced by the solar wind, such that reliable prediction of solar wind conditions in the near-Earth environment effectively reduces the impact of space weather on human society. Solar wind speed prediction is improved by making full use of OMNI data measured at Lagrangian Point 1 (L1) by the National Aeronautics and Space Administration (NASA) and image data observed by the Solar Dynamics Observatory (SDO) satellite in this work. Specifically, we propose a model based on the "two-dimensional attention mechanism" (TDAM) to predict solar wind speed. In this study, we first analyze and preprocess data from 2011 to 2017. Second, considering the characteristics of time series data, we adopt the gated recurrent units (GRU) model which can deal with long-term dependence as the prediction part of our model. Third, we design a TDAM, which enables our prediction network to focus on important parts. Three performance indices are used: root-mean-square error (RMSE), mean absolute error (MAE), and correlation coefficient (CC). By comparing TDAM with other models, we find that the TDAM model achieves the best prediction results, with RMSE of 62.8 km/s, MAE of 47.8 km/s, and CC of 0.789 24 h in advance. The experimental results show that the proposed TDAM model can improve the prediction accuracy of solar wind speed.
Funding OrganizationNational Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China
DOI10.1029/2020SW002707
WOS KeywordCORONAL HOLE
Language英语
Funding ProjectNational Science and Technology Major Project[2017-I-0007-0008] ; National Natural Science Foundation of China[61432011] ; National Natural Science Foundation of China[U1435212] ; National Natural Science Foundation of China[61105054]
Funding OrganizationNational Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China
WOS Research AreaAstronomy & Astrophysics ; Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences
WOS SubjectAstronomy & Astrophysics ; Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences
WOS IDWOS:000679063900001
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/76556
Collection中国科学院国家天文台
Corresponding AuthorXie, Zongxia
Affiliation1.Tianjin Univ, Coll Intelligence & Comp, Tianjin, Peoples R China
2.Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China
3.Chinese Acad Sci, Natl Astron Observ, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Sun, Yanru,Xie, Zongxia,Chen, Yanhong,et al. Solar Wind Speed Prediction With Two-Dimensional Attention Mechanism[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,2021,19(7):15.
APA Sun, Yanru,Xie, Zongxia,Chen, Yanhong,Huang, Xin,&Hu, Qinghua.(2021).Solar Wind Speed Prediction With Two-Dimensional Attention Mechanism.SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,19(7),15.
MLA Sun, Yanru,et al."Solar Wind Speed Prediction With Two-Dimensional Attention Mechanism".SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 19.7(2021):15.
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