Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
<p>To assist policymakers in making adequate decisions to stop the spread of the COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance. This paper presents a deep learning approach to forecast the cumulative number of COVID-19 cases using bidirectional L...
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| Main Author: | Ahmed Ben Said (14158926) (author) |
|---|---|
| Other Authors: | Abdelkarim Erradi (13475740) (author), Hussein Ahmed Aly (14151711) (author), Abdelmonem Mohamed (14151714) (author) |
| Published: |
2022
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| Subjects: | |
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