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딥러닝을 활용한 한반도 상공의대기굴절률예측.

Authors :
양준모
허 준
김정훈
박영주
추호성
박용배
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]

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