BAYESIAN DEEP LEARNING APPLIED TO LSTM MODELS FOR PREDICTING COVID-19 CONFIRMED CASES IN IRAQ

BAYESIAN DEEP LEARNING APPLIED TO LSTM MODELS FOR PREDICTING COVID-19 CONFIRMED CASES IN IRAQ

The COVID-19 pandemic has had a huge impact on populations around the world and has caused critical problems to medical systems. With the increasing number of COVID-19 infections, research has focused on forecasting the confirmed cases to make the right medical decisions. Despite the huge number of...

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Bibliographic Details
Main Authors:	Masoud Muhammed Hassan, Dozdar Ahmed
Format:	Article
Language:	English
Published:	University of Zakho 2023-04-01
Series:	Science Journal of University of Zakho
Subjects:	Deep learning, Bayesian Neural Networks, LSTM, Time-series data, forecasting, MC dropout.
Online Access:	https://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/1037

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