Algorithms | |
An Integrated Neural Network and SEIR Model to Predict COVID-19 | |
MohammadShahadat Hossain1  SharifNoor Zisad1  MohammedSazzad Hossain2  Karl Andersson3  | |
[1] Department of Computer Science and Engineering, University of Chittagong, Chittagong 4331, Bangladesh;Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka 1209, Bangladesh;Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, 93187 Skellefteå, Sweden; | |
关键词: COVID-19; coronavirus; SARS-CoV-2; 2019-nCoV; SEIR; neural network; | |
DOI : 10.3390/a14030094 | |
来源: DOAJ |
【 摘 要 】
A novel coronavirus (COVID-19), which has become a great concern for the world, was identified first in Wuhan city in China. The rapid spread throughout the world was accompanied by an alarming number of infected patients and increasing number of deaths gradually. If the number of infected cases can be predicted in advance, it would have a large contribution to controlling this pandemic in any area. Therefore, this study introduces an integrated model for predicting the number of confirmed cases from the perspective of Bangladesh. Moreover, the number of quarantined patients and the change in basic reproduction rate (the R
【 授权许可】
Unknown