A Machine Learning-Based Thermospheric Density Model with Uncertainty Quantification
Conventional thermospheric density models are limited in their ability to capture solar-geomagnetic coupling dynamics and lack probabilistic uncertainty estimates. We present MSIS-UN (NRLMSISE-00 with Uncertainty Quantification), an innovative framework integrating sparse principal component analysi...
Tallennettuna:
| Päätekijät: | , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2025-09-01
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| Sarja: | Atmosphere |
| Aiheet: | |
| Linkit: | https://www.mdpi.com/2073-4433/16/10/1120 |
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