Improved SEIR Model Based on Recovery Rate Optimization to Predict COVID-19
3rd Asia Conference on Computers and Communications, ACCC 2022
; : 29-34, 2022.
Article
in English
| Scopus | ID: covidwho-2306230
ABSTRACT
When using the traditional SEIR infectious disease model to predict the trend of novel coronavirus pneumonia epidemic, numerous initial parameters need to be tuned, and the parameters cannot change over time during the prediction process, which reduces the accuracy of the model. Firstly, thesis used a logistic model to preprocess the SEIR model parameters and proposed a SEIR model based on time series recovery rate optimization with a new parameter of effective immunity rate. Secondly, the model was trained with epidemic data from domestic and foreign provinces and cities, and the usability of the model was demonstrated experimentally, and the mean absolute percentage error (MAPE) and goodness of fit (R2) were used to compare with other models, which proved the superiority of the model prediction and indicated further research directions. © 2022 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
3rd Asia Conference on Computers and Communications, ACCC 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS