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...

Description complète

Enregistré dans:
Détails bibliographiques
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
Sujets:
COVID-19
Deep Learning
Prediction Model
Fine-tuning
Independently Recurrent Neural Network
Long-Short-Term-Memory
Electronic computers. Computer science
QA75.5-76.95
Accès en ligne:https://doaj.org/article/29562d9c71404cce9b11fd09ac22caaf
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Internet

https://doaj.org/article/29562d9c71404cce9b11fd09ac22caaf

Documents similaires