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Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting
Lu, J. Y.1; Jin, C. Q.1; Wang, M.1; Ji, H. S.2; Iluore, K.1; Guan, H. Y.3; Li, J. F.4; Li, J. Y.1
刊名SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
2019-04-01
卷号17期号:4页码:567-585
ISSN号1542-7390
DOI10.1029/2018SW002135
通讯作者Lu, J. Y.(jylu@nuist.edu.cn)
英文摘要One of the main issues of space weather is the timely prediction of disturbed solar wind parameters at L1, especially caused by Coronal Mass Ejection (CME). Using the data from 170 front halo, flare-associated CMEs, and in-site solar wind data, an analysis of the Interplanetary Coronal Mass Ejection (ICME) peak velocity at L1 related to associated coronal parameters is performed. The statistical methods including the Generalized Additive Modeling (GAM) and Multiple Collinear (MC) have been applied to explain the underlying physical reasons and set up a new prediction model. Our results indicate that (1) X-flare integral flux, CME linear velocity, and Acceleration observed on corona play key roles in ICME velocity, while other coronal parameters only present a weak correlation, such as the CME Mass and Angular Width, (2) the relationship between ICME velocity and CME Acceleration, as well as CME linear velocity, is nonstationary, and the ICME velocity will increase with the increasing CME Acceleration or linear velocity until saturation, and (3) MC is an effective method to improve the forecast model performance. Compared with 0.52 for only GAM, the correlation coefficient using GAM + MC reaches to 0.71. To further testify the prediction ability, the GAM + MC model results are compared with the Back-Propagation network model and a typically empirical statistic relation proposed by Manoharan (2006, https://doi.org/10.1007/s11207-006-0100-y; their correlation coefficients and root mean squared errors are both roughly 0.6 and 100 km/s, respectively). It is found that the MC + GAM can upgrade the forecast at least over 10%.
WOS关键词CORONAL MASS EJECTIONS ; SOLAR-WIND SPEED ; FLUX
WOS研究方向Astronomy & Astrophysics ; Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences
语种英语
出版者AMER GEOPHYSICAL UNION
WOS记录号WOS:000468190700005
内容类型期刊论文
源URL[http://libir.pmo.ac.cn/handle/332002/26688]  
专题中国科学院紫金山天文台
通讯作者Lu, J. Y.
作者单位1.Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Inst Space Weather, Nanjing, Jiangsu, Peoples R China
2.Purple Mt Observ, Nanjing, Jiangsu, Peoples R China
3.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing, Jiangsu, Peoples R China
4.Nanjing Univ Informat Sci & Technol, Sch Phys & Optoelect Engn, Nanjing, Jiangsu, Peoples R China
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GB/T 7714
Lu, J. Y.,Jin, C. Q.,Wang, M.,et al. Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,2019,17(4):567-585.
APA Lu, J. Y..,Jin, C. Q..,Wang, M..,Ji, H. S..,Iluore, K..,...&Li, J. Y..(2019).Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting.SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,17(4),567-585.
MLA Lu, J. Y.,et al."Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting".SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 17.4(2019):567-585.
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