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코로나 확진자 수 예측을 위한 BI-LSTM과 GRU 알고리즘의 성능 비교 분석.

Authors :
김재호
김장영
Source :
Journal of the Korea Institute of Information & Communication Engineering; Feb2022, Vol. 26 Issue 2, p187-192, 6p
Publication Year :
2022

Abstract

Even the announcing date for the staring date of “With Corona” has been decided, still many people have not completed vaccination, the most important condition for starting the With Corona, because of concerns for its side effects. In addition, although the economy may can be recovered by the With Corona, but the number of infected people may can be surged. In this paper, in order to awaken the people for the awareness of Corona 19 in advance of the With Corona, the Corona 19 is predicted through a non-linear probability process. Here, among the deep learning RNN, BI-LSTM, which is a bidirectional LSTM, and GRU, gates decreased than LSTM have been used. And this has been compared and analyzed through train set, test set, loss function, residual analysis, normal distribution, and autocorrelation, and compared and predicted for which has a better performance. [ABSTRACT FROM AUTHOR]

Details

Language :
Korean
ISSN :
22344772
Volume :
26
Issue :
2
Database :
Complementary Index
Journal :
Journal of the Korea Institute of Information & Communication Engineering
Publication Type :
Academic Journal
Accession number :
155586619
Full Text :
https://doi.org/10.6109/jkiice.2022.26.2.187