Prediction of COVID-19 epidemic situation via fine-tuned IndRNN

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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Autores principales: Zhonghua Hong, Ziyang Fan, Xiaohua Tong, Ruyan Zhou, Haiyan Pan, Yun Zhang, Yanling Han, Jing Wang, Shuhu Yang, Hong Wu, Jiahao Li
Formato: article
Lenguaje:EN
Publicado: PeerJ Inc. 2021
Materias:
COVID-19
Deep Learning
Prediction Model
Fine-tuning
Independently Recurrent Neural Network
Long-Short-Term-Memory
Electronic computers. Computer science
QA75.5-76.95
Acceso en línea:https://doaj.org/article/29562d9c71404cce9b11fd09ac22caaf
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https://doaj.org/article/29562d9c71404cce9b11fd09ac22caaf

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