83 citations as recorded by crossref.

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6. The use of sequential recurrent neural filters in forecasting the Dst index for the strong magnetic storm of autumn 2003 L. Ouarbya et al. 10.1016/j.aml.2011.12.002
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9. Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps J. Tian et al. 10.1016/j.asr.2004.06.017
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31. Operational models for forecasting Dst S. Watanabe et al. 10.1016/S0273-1177(02)00809-8
32. Prediction of solar and geomagnetic activity data using neural networks K. Macpherson et al. 10.1029/95JA02283
33. Estimating the geoeffectiveness of halo CMEs from associated solar and IP parameters using neural networks J. Uwamahoro et al. 10.5194/angeo-30-963-2012
34. Forecasting ionospheric structure during the great geomagnetic storms L. Cander & S. Mihajlovic 10.1029/97JA02418
35. Selection of the Main Control Parameters for the Dst Index Prediction Model Based on a Layer-wise Relevance Propagation Method Y. Li et al. 10.3847/1538-4365/ac616c
36. Cosmic ray variability and geomagnetic activity: A statistical study K. Kudela & M. Storini 10.1016/j.jastp.2005.02.018
37. Forecasting SYM‐H Index: A Comparison Between Long Short‐Term Memory and Convolutional Neural Networks F. Siciliano et al. 10.1029/2020SW002589
38. Prediction of horizontal component of earth's magnetic field over Indian sector using neural network model K. Unnikrishnan 10.1016/j.jastp.2014.06.014
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41. A neural network-based foF2 model for a single station in the polar cap R. Athieno et al. 10.1002/2016RS006192
42. Locally linear neurofuzzy modeling and prediction of geomagnetic disturbances based on solar wind conditions J. Sharifie et al. 10.1029/2005SW000209
43. Time series, neural networks and the future of the Sun A. Conway 10.1016/S1387-6473(98)00041-4
44. Neural network prediction of AE data J. Takalo & J. Timonen 10.1029/97GL02457
45. Auroral electrojet predictions with dynamic neural networks H. Gleisner & H. Lundstedt 10.1029/2001JA900046
46. What sustained multi-disciplinary research can achieve: The space weather modeling framework T. Gombosi et al. 10.1051/swsc/2021020
47. Neural network modeling of solar wind‐magnetosphere interaction J. Wu & H. Lundstedt 10.1029/97JA01081
48. A cellular automata-based model of Earth's magnetosphere in relation withDstindex A. Banerjee et al. 10.1002/2014SW001138
49. Incoherent radar spectrum processing using neural network R. Mueller et al. 10.1016/S0165-1684(98)00094-2
50. An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning R. Lin 林 et al. 10.3847/1538-4365/ad2dea
51. On the relation of the AE and PC indices J. Takalo & J. Timonen 10.1029/98JA02390
52. 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 10.1051/swsc/2019007
53. On the existence of a long range correlation in the Geomagnetic Disturbance storm time (Dst) index A. Banerjee et al. 10.1007/s10509-011-0836-1
54. Operational forecasts of the geomagnetic Dst index H. Lundstedt et al. 10.1029/2002GL016151
55. Comparison of neural network and support vector machine methods for Kp forecasting E. Ji et al. 10.1002/jgra.50500
56. Forecasting the Dst index using a swarm‐optimized neural network J. Lazzús et al. 10.1002/2017SW001608
57. A comparison of machine-learning techniques for the prediction of the auroral electrojet index S. Gopinath & P. Prince 10.1007/s12040-019-1194-6
58. Automatic detection of sudden commencements using neural networks A. Segarra & J. Curto 10.5047/eps.2012.12.011
59. Prediction of geomagnetic storm using neural networks: Comparison of the efficiency of the Satellite and ground-based input parameters M. Stepanova et al. 10.1088/1742-6596/134/1/012041
60. Transit clairvoyance: enhancingTESSfollow-up using artificial neural networks D. Kipping & C. Lam 10.1093/mnras/stw2974
61. Optimization of the neural‐network geomagnetic model for forecasting large‐amplitude substorm events V. Gavrishchaka & S. Ganguli 10.1029/2000JA900137
62. Prediction of Partial Ring Current Index Using LSTM Neural Network H. LI et al. 10.11728/cjss2022.05.210513061
63. Response of the auroral electrojets to the solar wind modeled with neural networks H. Gleisner & H. Lundstedt 10.1029/96JA03068
64. Model Evaluation Guidelines for Geomagnetic Index Predictions M. Liemohn et al. 10.1029/2018SW002067
65. Exploring Three Recurrent Neural Network Architectures for Geomagnetic Predictions P. Wintoft & M. Wik 10.3389/fspas.2021.664483
66. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting E. Camporeale 10.1029/2018SW002061
67. Purposeful Prediction of Space Weather Phenomena by Simulated Emotional Learning A. Gholipour et al. 10.1080/02286203.2004.11442288
68. A neural network prediction of solar cycle 23 A. Conway et al. 10.1029/98JA02539
69. Operational Dst index prediction model based on combination of artificial neural network and empirical model W. Park et al. 10.1051/swsc/2021021
70. Space weather modelling with intelligent hybrid systems: Predicting the solar wind velocity P. Wintoft & H. Lundstedt 10.1016/S0273-1177(97)01100-9
71. Investigating and comparing the two superstorms in the 23rd solar cycle F. Basciftci 10.1007/s12648-022-02396-y
72. Energy as a tracer of magnetospheric processes: GUMICS-4 global MHD results and observations compared T. Pulkkinen et al. 10.1016/j.jastp.2007.10.011
73. Empirical modeling of the storm time geomagnetic indices: a comparison between the local K and global Kp indices J. Uwamahoro & J. Habarulema 10.1186/1880-5981-66-95
74. Prediction of geomagnetic storms from solar wind data using Elman Recurrent Neural Networks J. Wu & H. Lundstedt 10.1029/96GL00259
75. Forbush Decreases and Geomagnetic Storms During a Highly Disturbed Solar and Interplanetary Period, 4–10 September 2017 B. Badruddin et al. 10.1029/2018SW001941
76. Prediction of the Dst Index with Bagging Ensemble-learning Algorithm S. Xu et al. 10.3847/1538-4365/ab880e
77. Multiple‐Hour‐Ahead Forecast of the Dst Index Using a Combination of Long Short‐Term Memory Neural Network and Gaussian Process M. Gruet et al. 10.1029/2018SW001898
78. Prediction of the Dst Index and Analysis of Its Dependence on Solar Wind Parameters Using Neural Network A. Lethy et al. 10.1029/2018SW001863
79. Dynamic Time Warping as a New Evaluation for Dst Forecast With Machine Learning B. Laperre et al. 10.3389/fspas.2020.00039
80. Neural network prediction of the AE index from the PC index J. Takalo & J. Timonen 10.1016/S1464-1917(98)00013-0
81. A neural network approach to the classification of electron and proton whistlers X. Miniere et al. 10.1016/0021-9169(95)00077-1
82. Using artificial neural networks in the investigation of four moderate geomagnetic storms (mGSs) that occurred in 2015 F. Basciftci 10.1016/j.asr.2023.01.001
83. Forecasting of the critical frequency of the ionosphereF2 layer by the method of artificial neural networks N. Barkhatov 10.1029/2004GI000065