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Identifying epidemic spreading dynamics of COVID-19 by pseudocoevolutionary simulated annealing optimizers
At the end of 2019, a new coronavirus (COVID-19) epidemic has triggered global public health concern. Here, a model integrating the daily intercity migration network, which constructed from real-world migration records and the Susceptible–Exposed–Infected–Removed model, is utilized to predict the ep...
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| Publicado en: | Neural Comput Appl |
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| Autores principales: | , , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Springer London
2020
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7429370/ https://ncbi.nlm.nih.gov/pubmed/32836902 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00521-020-05285-9 |
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