Propagation analysis and prediction of the COVID-19
| Autor: | Guanhua Chen, Haipeng Peng, Zihang Yang, Deyu Wang, Jiaxuan Zhang, Hao Tian Meng, Cui Meng, Jingze Huang, Zhongkai Dang, Lixiang Li |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Coronavirus disease 2019 (COVID-19) Computer science Process (computing) Populations and Evolution (q-bio.PE) Inference Virus diseases computer.software_genre Data modeling Computer Science - Computers and Society Transmission (telecommunications) FOS: Biological sciences Computers and Society (cs.CY) Data mining Quantitative Biology - Populations and Evolution computer |
| Popis: | Based on the official data modeling, this paper studies the transmission process of the Corona Virus Disease 2019 (COVID-19). The error between the model and the official data curve is within 3%. At the same time, it realized forward prediction and backward inference of the epidemic situation, and the relevant analysis help relevant countries to make decisions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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