47 citations as recorded by crossref.

1. Prediction of the Dst Index and Analysis of Its Dependence on Solar Wind Parameters Using Neural Network A. Lethy et al. https://doi.org/10.1029/2018SW001863
2. Recurrence‐Based Quantification of Dynamical Complexity in the Earth's Magnetosphere at Geospace Storm Timescales R. Donner et al. https://doi.org/10.1029/2018JA025318
3. Role of the variable solar wind in the dynamics of small-scale magnetosheath structures L. Rakhmanova et al. https://doi.org/10.3389/fspas.2023.1121230
4. Forecasting of global data‐binning parameters for high‐resolution empirical geomagnetic field models M. Sitnov et al. https://doi.org/10.1029/2012SW000783
5. The System Science Development of Local Time‐Dependent 40‐keV Electron Flux Models for Geostationary Orbit R. Boynton et al. https://doi.org/10.1029/2018SW002128
6. Real‐Time SWMF at CCMC: Assessing the Dst Output From Continuous Operational Simulations M. Liemohn et al. https://doi.org/10.1029/2018SW001953
7. Changes in and Recovery of the Turbulence Properties in the Magnetosheath for Different Solar Wind Streams L. Rakhmanova et al. https://doi.org/10.3390/universe10050194
8. A cellular automata-based model of Earth's magnetosphere in relation withDstindex A. Banerjee et al. https://doi.org/10.1002/2014SW001138
9. One-hour ahead prediction of the Dst index based on the optimum state space reconstruction and pattern recognition A. Bej et al. https://doi.org/10.1140/epjp/s13360-022-02687-7
10. Forecasting the Dst Index with Temporal Convolutional Network and Integrated Gradients J. Liu et al. https://doi.org/10.1007/s11207-024-02340-9
11. Probabilistic forecasting of the disturbance storm time index: An autoregressive Gaussian process approach M. Chandorkar et al. https://doi.org/10.1002/2017SW001627
12. Space Weather Effects Produced by the Ring Current Particles N. Ganushkina et al. https://doi.org/10.1007/s11214-017-0412-2
13. Forecasting the Dst index using a swarm‐optimized neural network J. Lazzús et al. https://doi.org/10.1002/2017SW001608
14. Forecasting of SYMH and ASYH indices for geomagnetic storms of solar cycle 24 including St. Patrick’s day, 2015 storm using NARX neural network A. Bhaskar & G. Vichare https://doi.org/10.1051/swsc/2019007
15. Online NARMAX model for electron fluxes at GEO R. Boynton et al. https://doi.org/10.5194/angeo-33-405-2015
16. Can We Estimate the Intensities of Great Geomagnetic Storms (ΔSYM-H ≤ −200 nT) with the Burton Equation or the O’Brien and McPherron Equation? M. Zhao et al. https://doi.org/10.3847/1538-4357/ac50a8
17. Forecasting Geomagnetic activity (Dst Index) using the ensemble kalman filter B. Nilam & S. Ram https://doi.org/10.1093/mnras/stac099
18. Sun-to-Mud observations of the May and October storms of 2024: impacts on Ireland’s Space Weather A. Fogg et al. https://doi.org/10.1051/swsc/2025044
19. System Identification of Local Time Electron Fluencies at Geostationary Orbit R. Boynton et al. https://doi.org/10.1029/2020JA028262
20. Prominence of the training data preparation in geomagnetic storm prediction using deep neural networks M. Cristoforetti et al. https://doi.org/10.1038/s41598-022-11721-8
21. Model Evaluation Guidelines for Geomagnetic Index Predictions M. Liemohn et al. https://doi.org/10.1029/2018SW002067
22. Dst Index Forecast Based on Ground‐Level Data Aided by Bio‐Inspired Algorithms J. Lazzús et al. https://doi.org/10.1029/2019SW002215
23. Electron flux models for different energies at geostationary orbit R. Boynton et al. https://doi.org/10.1002/2016SW001506
24. Features of turbulent cascade development in the magnetosheath during ICME L. Rakhmanova et al. https://doi.org/10.12737/stp-113202502
25. A Dynamical Model of Equatorial Magnetosonic Waves in the Inner Magnetosphere: A Machine Learning Approach R. Boynton et al. https://doi.org/10.1029/2020JA028439
26. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting E. Camporeale https://doi.org/10.1029/2018SW002061
27. Evaluation ofKpandDstPredictions Using ACE and DSCOVR Solar Wind Data P. Wintoft & M. Wik https://doi.org/10.1029/2018SW001994
28. Modeling the time behavior of the D st index during the main phase of magnetic storms generated by various types of solar wind N. Nikolaeva et al. https://doi.org/10.1134/S0010952513060038
29. A General Use QSAR-ARX Model to Predict the Corrosion Inhibition Efficiency of Drugs in Terms of Quantum Mechanical Descriptors and Experimental Comparison for Lidocaine C. Beltran-Perez et al. https://doi.org/10.3390/ijms23095086
30. Comparison of Dst forecast models for intense geomagnetic storms E. Ji et al. https://doi.org/10.1029/2011JA016872
31. Electron Flux Dropouts at L ∼ 4.2 From Global Positioning System Satellites: Occurrences, Magnitudes, and Main Driving Factors R. Boynton et al. https://doi.org/10.1002/2017JA024523
32. Geomagnetic storm forecasting service StormFocus: 5 years online T. Podladchikova et al. https://doi.org/10.1051/swsc/2018017
33. Forecasting SYM‐H Index: A Comparison Between Long Short‐Term Memory and Convolutional Neural Networks F. Siciliano et al. https://doi.org/10.1029/2020SW002589
34. On the prediction of the auroral westward electrojet index O. Amariutei & N. Ganushkina https://doi.org/10.5194/angeo-30-841-2012
35. The Influence of Solar Wind and Geomagnetic Indices on Lower Band Chorus Emissions in the Inner Magnetosphere R. Boynton et al. https://doi.org/10.1029/2018JA025704
36. Statistical Study between Characteristic Parameters of Coronal Holes and Intensity/Time of Geomagnetic Storms X. BU et al. https://doi.org/10.11728/cjss2020.01.009
37. Space‐Based Sentinels for Measurement of Infrared Cooling in the Thermosphere for Space Weather Nowcasting and Forecasting M. Mlynczak et al. https://doi.org/10.1002/2017SW001757
38. Extended geomagnetic storm forecast ahead of available solar wind measurements T. Podladchikova & A. Petrukovich https://doi.org/10.1029/2012SW000786
39. 25 Years of Self-Organized Criticality: Solar and Astrophysics M. Aschwanden et al. https://doi.org/10.1007/s11214-014-0054-6
40. Application of nonlinear autoregressive moving average exogenous input models to geospace: advances in understanding and space weather forecasts R. Boynton et al. https://doi.org/10.5194/angeo-31-1579-2013
41. Assessing Dst prediction models for forecasting the geoeffectiveness of ICME structures S. Balan et al. https://doi.org/10.1007/s12036-025-10082-8
42. Statistical Prediction of Dst Index by Solar Wind Data and <inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula>-Distributions P. Qin & R. Nishii https://doi.org/10.1109/TPS.2015.2485661
43. Dependence of geomagnetic activity during magnetic storms on solar-wind parameters for different types of streams: 4. Simulation for magnetic clouds N. Nikolaeva et al. https://doi.org/10.1134/S0016793214020145
44. Features of turbulent cascade development in the magnetosheath during ICME L. Rakhmanova et al. https://doi.org/10.12737/szf-113202502
45. Decoding solar wind-magnetosphere coupling M. Beharrell & F. Honary https://doi.org/10.1002/2016SW001467
46. Exploring Three Recurrent Neural Network Architectures for Geomagnetic Predictions P. Wintoft & M. Wik https://doi.org/10.3389/fspas.2021.664483
47. Prediction of Partial Ring Current Index Using LSTM Neural Network H. LI et al. https://doi.org/10.11728/cjss2022.05.210513061