Open AccessPrediction of COVID-19 epidemic situation via fine-tuned IndRNN
Author(s) -
Zhonghua Hong,
Ziyang Fan,
Xiaohua Tong,
Ruyan 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
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