Meet ApplyKite Twin, the application assistant that learns with you
Meet your Twin, it learns with you
Your Twin learns with you
Launch week codes:30% off annual Pro20% off monthly Pro
Ends in00h00m00s
Ends in00h00m00s
Xiangning Chu
Research Interests
Make your next move.
Prepare your application
Review drafts before you send them.
Explore related searches
Articles (13)
Year:
2025
Year:
2025
Year:
2025
Year:
2025
We investigate the response of outer radiation belt electron fluxes to different solar wind and geomagnetic indices using an interpretable machine learning method. We reconstruct the electron flux variation during 19 enhancement and 7 depletion events and demonstrate the feature attribution analysis called SHAP (SHapley Additive exPlanations) on the superposed epoch results for the first time. We find that the intensity and duration of the substorm sequence following an initial dropout determine the overall enhancement or depletion of electron fluxes, while the solar wind pressure drives the initial dropout in both types of events. Further statistical results from a data set with 71 events confirm this and show a significant correlation between the resulting flux levels and the average AL index, indicating that the observed “depletion” event can be more accurately described as a “non‐enhancement” event. Our novel SHAP‐Enhanced Superposed Epoch Analysis (SHESEA) method can offer insight in various physical systems.
Year:
2024
Year:
2022
Year:
2021
Year:
2021
Year:
2021
Year:
2020
Year:
2020
Year:
2020
Year:
2020
Collaborators (4)
Robert McPherron
Professor
University of California, Los Angeles
XINLIN LI
University of Colorado Boulder
Zhenguang Huang
University of Science and Technology of China
Mihailo Martinović
Resarcher / Scientist
University of Arizona
Make your next move.
Prepare your application
Review drafts before you send them.