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딥러닝을 활용한 한반도 상공의대기굴절률예측.
- Source :
- Journal of Korean Institute of Electromagnetic Engineering & Science / Han-Guk Jeonjapa Hakoe Nonmunji; Jun2023, Vol. 34 Issue 6, p493-496, 4p
- Publication Year :
- 2023
-
Abstract
- In this study, we propose a model for predicting atmospheric refractivity using meteorological data and deep learning. The purpose of this study is to compare the prediction accuracy of traditional interpolation methods and the proposed model, verify whether the deep learning model trained on meteorological data can provide values closer to the true values, and thus demonstrate the potential for utilizing deep learning in predicting atmospheric refractivity. [ABSTRACT FROM AUTHOR]
- Subjects :
- DEEP learning
ATMOSPHERIC radio refractivity
ATMOSPHERIC models
INTERPOLATION
Subjects
Details
- Language :
- Korean
- ISSN :
- 12263133
- Volume :
- 34
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Journal of Korean Institute of Electromagnetic Engineering & Science / Han-Guk Jeonjapa Hakoe Nonmunji
- Publication Type :
- Academic Journal
- Accession number :
- 167449127
- Full Text :
- https://doi.org/10.5515/KJKIEES.2023.34.6.493