An intelligent prediction model of epidemic characters based on multi-feature
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY(2024)
Abstract
The epidemic characters of Omicron (e.g. large-scale transmission) are significantly different from the initial variants of COVID-19. The data generated by large-scale transmission is important to predict the trend of epidemic characters. However, the results of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission. In consequence, these inaccurate results have negative impacts on the process of the manufacturing and the service industry, for example, the production of masks and the recovery of the tourism industry. The authors have studied the epidemic characters in two ways, that is, investigation and prediction. First, a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters. Second, the beta-SEIDR model is established, where the population is classified as Susceptible, Exposed, Infected, Dead and beta-Recovered persons, to intelligently predict the epidemic characters of COVID-19. Note that beta-Recovered persons denote that the Recovered persons may become Susceptible persons with probability beta. The simulation results show that the model can accurately predict the epidemic characters.
MoreTranslated text
Key words
artificial intelligence,big data,data analysis,evaluation,feature extraction,intelligent information processing,medical applications
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined