Issue |
J. Space Weather Space Clim.
Volume 9, 2019
System Science: Application to Space Weather Analysis, Modelling, and Forecasting
|
|
---|---|---|
Article Number | A19 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/swsc/2019020 | |
Published online | 10 June 2019 |
- Alves MV, Echer E, Gonzalez WD. 2006. Geoeffectiveness of corotating interaction regions as measured by Dst index. J Geophys Res (Space Phys) 111: A07S05. DOI: 10.1029/2005JA011379. [Google Scholar]
- Ayala Solares JR, Wei H-L, Boynton RJ, Walker SN, Billings SA. 2016. Modeling and prediction of global magnetic disturbance in near-Earth space: A case study for Kp index using NARX models. Space Weather 14(10): 899. DOI: 10.1002/2016sw001463. [CrossRef] [Google Scholar]
- Balikhin MA, Boynton RJ, Walker SN, Borovsky JE, Billings SA, Wei HL. 2011. Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit. Geophys Res Lett 38(18): L18105. DOI: 10.1029/2011gl048980. [CrossRef] [Google Scholar]
- Bartels J. 1949. The standardized index, Ks, and the planetary index, Kp. IATME Bull 12b 97: 2021. [Google Scholar]
- Boberg F, Wintoft P, Lundstedt H. 2000. Real time Kp predictions from solar wind data using neural networks. Phys Chem Earth Part C: Solar Terr Planet Sci 25(4): 275–280. [Google Scholar]
- Burch JL, Torbert RB, Phan TD, Chen L-J, Moore TE, et al. 2016. Electron-scale measurements of magnetic reconnection in space. Science 352(6290): L03803. DOI: 10.1126/science.aaf2939, URL http://science.sciencemag.org/content/352/6290/aaf2939. [CrossRef] [Google Scholar]
- Dungey JW. 1961. Interplanetary magnetic field and the auroral zones. Phys Rev Lett 6(2): 47. [Google Scholar]
- Gonzalez WD, Tsurutani BT. 1987. Criteria of interplanetary parameters causing intense magnetic storms (Dst < −100 nT). Planet Space Sci 35(9): 1101–1109. DOI: 10.1016/0032-0633(87)90015-8, URL http://www.sciencedirect.com/science/article/pii/0032063387900158. [NASA ADS] [CrossRef] [Google Scholar]
- Gu Y, Wei H-L, Boynton RJ, Walker SN, Balikhin MA. 2017. Prediction of Kp index using NARMAX models with a robust model structure selection method. In: 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Targoviste, Romania, 29 June–1 July 2017. DOI: 10.1109/ecai.2017.8166414. [Google Scholar]
- Han H, Wang W-Y, Mao B-H. 2005. Borderline-SMOTE: a new over-sampling method in imbalanced data sets learning. In: International Conference on Intelligent Computing, Hefei, China, August 23–26, 2005. [Google Scholar]
- Hellweg CE, Baumstark-Khan C. 2007. Getting ready for the manned mission to Mars: the astronauts risk from space radiation. Naturwissenschaften 94(7): 517–526. [CrossRef] [Google Scholar]
- Johnson JR, Wing S. 2005. A solar cycle dependence of nonlinearity in magnetospheric activity. J Geophys Res: Space Phys 110(A4): A04211. DOI: 10.1029/2004JA010638, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2004JA010638. [Google Scholar]
- Kaastra I, Boyd M. 1996. Designing a neural network for forecasting financial and economic time series. Neurocomputing 10(3): 215–236. DOI: 10.1016/0925-2312(95)00039-9. [CrossRef] [Google Scholar]
- Karunasinghe DS, Liong S-Y. 2006. Chaotic time series prediction with a global model: Artificial neural network. J Hydrol 323(1–4): 92–105. DOI: 10.1016/j.jhydrol.2005.07.048. [CrossRef] [Google Scholar]
- Kilpua E, Koskinen HEJ, Pulkkinen TI. 2017. Coronal mass ejections and their sheath regions in interplanetary space. Living Rev Solar Phys 14(1): 5. DOI: 10.1007/s41116-017-0009-6. [Google Scholar]
- Kutiev I, Muhtarov P, Andonov B, Warnant R. 2009. Hybrid model for nowcasting and forecasting the K index. J Atmos Solar-Terr Phys 71(5): 589–596. [CrossRef] [Google Scholar]
- Lapedes A, Farber R. 1987. Nonlinear signal processing using neural networks: Prediction and system modelling. Los Alamos National Laboratory Tech Report LA-UR87-2662. [Google Scholar]
- MATLAB. 2014. Version 8.4 (R2014b), The MathWorks Inc, Natick, MA. [Google Scholar]
- Pudovkin MI, Shukhtina MA, Poniavin DI, Zaitseva SA, Ivanov OU. 1980. On the geoefficiency of the solar wind parameters. Ann Geophys 36: 549–553. [Google Scholar]
- Rasttter L, Kuznetsova MM, Glocer A, Welling D, Meng X, et al. 2013. Geospace environment modeling 2008–2009 challenge: Dst index. Space Weather 11(4): 187–205. DOI: 10.1002/swe.20036. [CrossRef] [Google Scholar]
- Samuel AL. 1959. Some studies in machine learning using the game of checkers. IBM J Res Dev 3(3): 210–229. DOI: 10.1147/rd.33.0210. [CrossRef] [Google Scholar]
- Shibata K, Magara T. 2011. Solar flares: Magnetohydrodynamic processes. Living Rev Solar Phys 8(6). DOI: 10.1007/lrsp-2011-6, URL http://www.livingreviews.org/lrsp-2011-6. [CrossRef] [Google Scholar]
- Stearns SD. 1985. Adaptive signal processing. [Google Scholar]
- Wei H-L, Billings SA, Sharma AS, Wing S, Boynton RJ, Walker SN. 2011. Forecasting relativistic electron flux using dynamic multiple regression models. Ann Geophys 29(2): 415–420. DOI: 10.5194/angeo-29-415-2011. [CrossRef] [Google Scholar]
- Werbos PJ. 1990. Backpropagation through time: What it does and how to do it. Proc IEEE 78(10): 1550–1560. [CrossRef] [Google Scholar]
- Wilson RM. 1987. Geomagnetic response to magnetic clouds. Planet Space Sci 35(3): 329–335. DOI: 10.1016/0032-0633(87)90159-0, URL http://www.sciencedirect.com/science/article/pii/0032063387901590. [CrossRef] [Google Scholar]
- Wing S, Johnson JR, Jen J, Meng C-I, Sibeck DG, et al. 2005. Kp forecast models. J Geophys Res: Space Phys 110(A4). DOI: 10.1029/2004ja010500. [Google Scholar]
- Wrenn GL. 1995. Conclusive evidence for internal dielectric charging anomalies on geosynchronous communications spacecraft. J Spacecraft Rockets 32(3): 514–520. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.