z-logo
open-access-imgOpen Access
Prediction of COVID-19 epidemic situation via fine-tuned IndRNN
Author(s) -
Zhonghua Hong,
Fan Zhai,
Xiaohua Tong,
Ri-Gui Zhou,
Haiyan Pan,
Yun Zhang,
Yanling Han,
Jing Wang,
Shuhu Yang,
Hong Wu,
Jiahao Li
Publication year - 2021
Publication title -
peerj. computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.806
H-Index - 24
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.770
Subject(s) - covid-19 , mean absolute percentage error , mean squared error , government (linguistics) , china , pandemic , artificial neural network , statistics , computer science , phase (matter) , econometrics , operations research , artificial intelligence , geography , mathematics , medicine , linguistics , philosophy , disease , archaeology , pathology , infectious disease (medical specialty) , chemistry , organic chemistry

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here