34 citations as recorded by crossref.

1. Long-term Spatial and Temporal Variations of Aurora Borealis Events in the Period 1700 – 1905 M. Vázquez et al. https://doi.org/10.1007/s11207-013-0413-6
2. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting E. Camporeale https://doi.org/10.1029/2018SW002061
3. Strong geomagnetic activity forecast by neural networks under dominant southern orientation of the interplanetary magnetic field F. Valach et al. https://doi.org/10.1016/j.asr.2013.12.005
4. Geoeffectiveness of Coronal Mass Ejections in the SOHO Era M. Dumbović et al. https://doi.org/10.1007/s11207-014-0613-8
5. Prediction of intensity of moderate and intense geomagnetic storms using artificial neural network during two complete solar cycles 23 and 24 P. Singh https://doi.org/10.1007/s12648-021-02192-0
6. Heart disease prediction using distinct artificial intelligence techniques: performance analysis and comparison M. Hossain et al. https://doi.org/10.1007/s42044-023-00148-7
7. A Review of the Logistic Regression Model with Emphasis on Medical Research E. Boateng & D. Abaye https://doi.org/10.4236/jdaip.2019.74012
8. Intelligent prediction model for geoeffectiveness of coronal mass ejections X. Tang et al. https://doi.org/10.3389/fspas.2026.1839173
9. Space Weather: Physics, Effects and Predictability A. Singh et al. https://doi.org/10.1007/s10712-010-9103-1
10. On the prediction of geoeffectiveness of CMEs during the ascending phase of SC24 using a logistic regression method D. Besliu-Ionescu et al. https://doi.org/10.1016/j.jastp.2019.04.017
11. Relation of CME Speed and Magnetic Helicity in CME Source Regions on the Sun during the Early Phase of Solar Cycles 23 and 24 R. Kim et al. https://doi.org/10.1007/s11207-017-1079-2
12. 基于机器学习方法的短期太阳爆发活动预报模型综述 鑫. 黄 et al. https://doi.org/10.1360/N072023-0208
13. Validation of the CME Geomagnetic Forecast Alerts Under the COMESEP Alert System M. Dumbović et al. https://doi.org/10.1007/s11207-017-1120-5
14. Predicting the Geoeffectiveness of CMEs Using Machine Learning A. Pricopi et al. https://doi.org/10.3847/1538-4357/ac7962
15. Aurorae Observed at the Canary Islands M. Vázquez & J. Vaquero https://doi.org/10.1007/s11207-010-9650-0
16. An Improved Halo Coronal Mass Ejection Geoeffectiveness Prediction Model Using Multiple Coronal Mass Ejection Features Based on the DC-PCA-KNN Method D. Ye et al. https://doi.org/10.3847/1538-4357/ad98f0
17. A Review on Logistic Regression in Medical Research N. Panda https://doi.org/10.55489/njcm.134202222
18. The physics of space weather/solar-terrestrial physics (STP): what we know now and what the current and future challenges are B. Tsurutani et al. https://doi.org/10.5194/npg-27-75-2020
19. Solar energetic particle flux enhancement as a predictor of geomagnetic activity in a neural network‐based model F. Valach et al. https://doi.org/10.1029/2008SW000421
20. Relationship between interplanetary field/plasma parameters with geomagnetic indices and their behavior during intense geomagnetic storms N. Joshi et al. https://doi.org/10.1016/j.newast.2011.01.004
21. Regression modeling method of space weather prediction A. Parnowski https://doi.org/10.1007/s10509-009-0060-4
22. A study on precursors leading to geomagnetic storms using artificial neural network G. SINGH & A. SINGH https://doi.org/10.1007/s12040-016-0702-1
23. Space weather: the history of research and forecasting A. Parnowski et al. https://doi.org/10.15407/knit2010.01.090
24. A New Method for Predicting Non‐Recurrent Geomagnetic Storms C. Wang et al. https://doi.org/10.1029/2023SW003522
25. Robust Estimators of Logistic Regression with Problems Multicollinearity or Outliers Values. F. AL- Aabdi & R. AL – Shaibani https://doi.org/10.31642/JoKMC/2018/0202010
26. Nitric oxide cooling emission during geomagnetic storm: Case studies T. Bag et al. https://doi.org/10.1016/j.asr.2023.09.064
27. Estimating the geoeffectiveness of halo CMEs from associated solar and IP parameters using neural networks J. Uwamahoro et al. https://doi.org/10.5194/angeo-30-963-2012
28. A neural network Dst index model driven by input time histories of the solar wind–magnetosphere interaction M. Revallo et al. https://doi.org/10.1016/j.jastp.2014.01.011
29. Impacts of CMEs on Earth Based on Logistic Regression and Recommendation Algorithm Y. Shi et al. https://doi.org/10.34133/2022/9852185
30. Geoeffectiveness Prediction of CMEs D. Besliu-Ionescu & M. Mierla https://doi.org/10.3389/fspas.2021.672203
31. The challenge of predicting the occurrence of intense storms N. Srivastava https://doi.org/10.1007/BF02702526
32. Short-term solar eruptive activity prediction models based on machine learning approaches: A review X. Huang et al. https://doi.org/10.1007/s11430-023-1375-2
33. Geoeffectiveness of XRA events associated with RSP II and/or RSP IV estimated using the artificial neural network F. Valach et al. https://doi.org/10.1007/s11200-007-0032-5
34. Source region of the 18 November 2003 coronal mass ejection that led to the strongest magnetic storm of cycle 23 N. Srivastava et al. https://doi.org/10.1029/2008JA013845