15 citations as recorded by crossref.

1. Artificial neural network technique for predicting the critical frequency of the ionospheric F 2 layer N. Barkhatov et al. 10.1007/s11141-005-0043-4
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4. Progress in space weather predictions and applications H. Lundstedt 10.1016/j.asr.2003.09.072
5. Forecasting of the critical frequency of the ionosphereF2 layer by the method of artificial neural networks N. Barkhatov 10.1029/2004GI000065
6. Forecasting ionospheric structure during the great geomagnetic storms L. Cander & S. Mihajlovic 10.1029/97JA02418
7. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting E. Camporeale 10.1029/2018SW002061
8. Forecasting Solar Cycle 25 with Physical Model-Validated Recurrent Neural Networks A. Espuña Fontcuberta et al. 10.1007/s11207-022-02104-3
9. Predicting the Functional Dependence of the Sunspot Number in the Solar Activity Cycle Based on Elman Artificial Neural Network I. Krasheninnikov & S. Chumakov 10.1134/S0016793222600904
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11. Recovery of missing information in graph sequences by means of reference pattern matching and decision tree learning H. Bunke et al. 10.1016/j.patcog.2005.10.011
12. Prediction of the maximum observed frequency of the ionospheric HF radio channel using the method of artificial neural networks N. Barkhatov et al. 10.1134/S0016793206010099
13. Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network Y. Yang et al. 10.1029/2018SW001955
14. Forecasting the solar cycle 25 using a multistep Bayesian neural network I. Bizzarri et al. 10.1093/mnras/stac2013
15. Forecasting Solar Cycle 25 Using Deep Neural Networks B. Benson et al. 10.1007/s11207-020-01634-y