Using Unsupervised and Supervised Machine Learning Methods to Correct Offset Anomalies in the GOES‐16 Magnetometer Data
Abstract This study uses supervised and unsupervised machine learning (ML) methods to correct unwanted offsets observed in the NOAA GOES‐16 magnetometer data. All GOES satellites have an inboard and outboard magnetometer sensor mounted along a long boom. Post‐launch testing of the GOES‐16 magnetomet...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Wiley
2021-12-01
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| シリーズ: | Space Weather |
| オンライン･アクセス: | https://doi.org/10.1029/2021SW002892 |
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