| Autor: |
Pieter Bastiaan Ober, Jiri Doubek, Tamás Prajczer, János Nemes, Csongor Fekete, Mickael Dall’Orso, Guillaume Buscarlet |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Engineering Proceedings, Vol 54, Iss 1, p 48 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2673-4591 |
| DOI: |
10.3390/ENC2023-15456 |
| Popis: |
The paper describes the development of a machine learning-based system to predict the performance of EGNOS. The system is shown to perform considerably better than existing simple geometry-based ‘macro’ models developed for the same purpose in the past. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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