92 citations as recorded by crossref.

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48. Dst Index Forecast Based on Ground‐Level Data Aided by Bio‐Inspired Algorithms J. Lazzús et al. https://doi.org/10.1029/2019SW002215
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52. Geomagnetic storm predictions from solar wind data with the use of dynamic neural networks J. Wu & H. Lundstedt https://doi.org/10.1029/97JA00975
53. Purposeful Prediction of Space Weather Phenomena of Simulated Emotional Learning A. Gholipour et al. https://doi.org/10.2316/Journal.205.2004.2.205-4121
54. Learning based brain emotional intelligence as a new aspect for development of an alarm system T. Babaie et al. https://doi.org/10.1007/s00500-007-0258-8
55. Black box modeling of magnetospheric dynamics to forecast geomagnetic activity A. Gholipour et al. https://doi.org/10.1029/2003SW000039
56. RMSE is not enough: Guidelines to robust data-model comparisons for magnetospheric physics M. Liemohn et al. https://doi.org/10.1016/j.jastp.2021.105624
57. <i>Dst</i> Index Prediction Method Based on LSTM Neural Network S. LI et al. https://doi.org/10.11728/cjss2025.03.2024-0045
58. Neural network model for predicting the horizontal component of Earth’s magnetic field (H) over Indian equatorial region during quiet and disturbed periods S. Sajith Babu et al. https://doi.org/10.1016/j.asr.2024.12.014
59. On the application of information theory to the optimum state-space reconstruction of the short-term solar radio flux (10.7 cm), and its prediction via a neural network T. Chatterjee https://doi.org/10.1046/j.1365-8711.2001.04110.x
60. Solar origin of geomagnetic storms and prediction of storms with the use of neural networks H. Lundstedt https://doi.org/10.1007/BF01888978
61. Daily geomagnetic field prediction of INTERMAGNET observatories data using the multilayer perceptron neural network S. Ouadfeul et al. https://doi.org/10.1007/s12517-014-1308-z
62. Twenty‐four hour predictions of f0F2 using time delay neural networks P. Wintoft & L. Cander https://doi.org/10.1029/1998RS002149
63. Operational models for forecasting Dst S. Watanabe et al. https://doi.org/10.1016/S0273-1177(02)00809-8
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66. A neural network study of the mapping from solar magnetic fields to the daily average solar wind velocity P. Wintoft & H. Lundstedt https://doi.org/10.1029/1998JA900183
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75. Automatic detection of sudden commencements using neural networks A. Segarra & J. Curto https://doi.org/10.5047/eps.2012.12.011
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78. Prediction of Partial Ring Current Index Using LSTM Neural Network H. LI et al. https://doi.org/10.11728/cjss2022.05.210513061
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80. Model Evaluation Guidelines for Geomagnetic Index Predictions M. Liemohn et al. https://doi.org/10.1029/2018SW002067
81. Exploring Three Recurrent Neural Network Architectures for Geomagnetic Predictions P. Wintoft & M. Wik https://doi.org/10.3389/fspas.2021.664483
82. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting E. Camporeale https://doi.org/10.1029/2018SW002061
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87. Prediction of geomagnetic storms from solar wind data using Elman Recurrent Neural Networks J. Wu & H. Lundstedt https://doi.org/10.1029/96GL00259
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92. Forecasting of the critical frequency of the ionosphereF2 layer by the method of artificial neural networks N. Barkhatov https://doi.org/10.1029/2004GI000065