23 citations as recorded by crossref.

1. Three‐dimensional MHD modeling of the solar wind structures associated with 13 December 2006 coronal mass ejection R. Kataoka et al. 10.1029/2009JA014167
2. Dynamics of the Radiation Environment in the Near-Earth Space in September–November 2020 according to the Meteor-M and Electro-L Satellite Data I. Myagkova et al. 10.1134/S0010952521060071
3. Space Weather Effects from Observations by Moscow University Cubesat Constellation A. Bogomolov et al. 10.3390/universe8050282
4. Geosynchronous Relativistic Electron Events Associated with High-Speed Solar Wind Streams in 2006 S. Lee et al. 10.5140/JASS.2009.26.4.439
5. Prediction of the Dst Geomagnetic Index Using Adaptive Methods I. Myagkova et al. 10.3103/S1068373921030031
6. New hemispheric geomagnetic indicesαwith 15 min time resolution A. Chambodut et al. 10.1002/2015JA021479
7. The Use of Coupling Functions in the Forecasting of the Dst-Index Amplitude with Adaptive Methods I. Myagkova et al. 10.1134/S0016793220060092
8. Effects of nonlinear wave growth on extreme radiation belt electron fluxes D. Summers et al. 10.1029/2011JA016602
9. Prediction of geomagnetic indexes with the help of artificial neural networks I. Myagkova et al. 10.1051/e3sconf/20172002011
10. TID evaluation based on variabilities of space radiation and device failure dose in typical navigation satellite orbits J. Wang et al. 10.1016/j.microrel.2022.114747
11. Comparison of the Efficiency of Machine Learning Methods in Studying the Importance of Input Features in the Problem of Forecasting the Dst Geomagnetic Index R. Vladimirov et al. 10.1134/S0016793222600795
12. The Significance of Input Features for Domain Adaptation of Spacecraft Data E. Karimov et al. 10.31857/S0023420623600125
13. Using Classification Methods in Forecasting the Level of Geomagnetic Field Disturbance Based on the Kp-Index I. Gadzhiev et al. 10.1134/S0016793224600140
14. Solar cycle variations of outer radiation belt and its relationship to solar wind structure dependences Y. Miyoshi & R. Kataoka 10.1016/j.jastp.2010.09.031
15. Why are relativistic electrons persistently quiet at geosynchronous orbit in 2009? R. Kataoka & Y. Miyoshi 10.1029/2010SW000571
16. Comparison of the Efficiency of Machine Learning Methods in Studying the Importance of Input Features in the Problem of Forecasting the Dst Geomagnetic Index R. Vladimirov et al. 10.31857/S0016794022100224
17. An overview of RADOM results for earth and moon radiation environment on Chandrayaan-1 satellite T. Dachev et al. 10.1016/j.asr.2011.05.009
18. An unusual long‐lived relativistic electron enhancement event excited by sequential CMEs X. Yang et al. 10.1002/2014JA019797
19. Analysis of the Earth's magnetosphere states using the algorithm of adaptive construction of hierarchical neural network classifiers S. Dolenko et al. 10.1051/e3sconf/20172002001
20. The K‐derived MLT sector geomagnetic indices A. Chambodut et al. 10.1002/grl.50947
21. The Prediction of the Dst-Index Based on Machine Learning Methods A. Efitorov et al. 10.1134/S0010952518060035
22. Extreme relativistic electron fluxes at geosynchronous orbit: Analysis of GOESE> 2 MeV electrons N. Meredith et al. 10.1002/2014SW001143
23. The Significance of Input Features for Domain Adaptation of Spacecraft Data E. Karimov et al. 10.1134/S0010952523700466