Prediction of COVID-19 epidemic situation via fine-tuned IndRNN
The COVID-19 pandemic is the most serious catastrophe since the Second World War. To predict the epidemic more accurately under the influence of policies, a framework based on Independently Recurrent Neural Network (IndRNN) with fine-tuning are proposed for predict the epidemic development trend of...
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| Auteurs principaux: | Zhonghua Hong, Ziyang Fan, Xiaohua Tong, Ruyan Zhou, Haiyan Pan, Yun Zhang, Yanling Han, Jing Wang, Shuhu Yang, Hong Wu, Jiahao Li |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
PeerJ Inc.
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/29562d9c71404cce9b11fd09ac22caaf |
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