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Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application
Machine learning (ML) has been applied to space weather problems with increasing frequency in recent years, driven by an influx of in-situ measurements and a desire to improve modeling and forecasting capabilities throughout the field. Space weather originates from solar perturbations and is compris...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068719/ https://www.ncbi.nlm.nih.gov/pubmed/35508465 http://dx.doi.org/10.1038/s41598-022-11049-3 |