Relativistic Electron Model in the Outer Radiation Belt Using a Neural Network Approach

@article{Chu2021RelativisticEM,
  title={Relativistic Electron Model in the Outer Radiation Belt Using a Neural Network Approach},
  author={Xiangning Chu and Donglai Ma and Jacob Bortnik and W. Kent Tobiska and Alfredo Cruz and S. Dave Bouwer and Hong Zhao and Qianli Ma and Kun Zhang and Daniel N. Baker and Xinlin Li and Harlan E. Spence and G. Reeves},
  journal={Space Weather},
  year={2021},
  volume={19}
}
We present a machine‐learning‐based model of relativistic electron fluxes >1.8 MeV using a neural network approach in the Earth's outer radiation belt. The Outer RadIation belt Electron Neural net model for Relativistic electrons (ORIENT‐R) uses only solar wind conditions and geomagnetic indices as input. For the first time, we show that the state of the outer radiation belt can be determined using only solar wind conditions and geomagnetic indices, without any initial and boundary conditions… 

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