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Enhancing COVID‐19 Forecasting Accuracy in Malaysia Using a Hybrid ARIMA‐LSTM Model With Exogenous Variables: A Time‐Series Predictive Study

ABSTRACT Background Accurate forecasting of COVID‐19 cases is essential for effective public health planning and resource allocation. Traditional statistical and deep‐learning models often fail to jointly capture linear dynamics, nonlinear patterns, and exogenous drivers of disease transmission. Thi...

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Main Authors: Al Mahmud, Kamarul Imran Musa, Firdaus Mohamad Hamzah, Zainab Mat Yudin Badrin, Mohamad Arif Awang Nawi
Format: Artigo
Language:Inglês
Published: Wiley 2026-06-01
Series:Health Science Reports
Subjects:
ARIMA
COVID‐19
LSTM
machine learning
time series forecasting
Online Access:https://doi.org/10.1002/hsr2.72684
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