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  • 标题:Prediction model of COVID 19 based on two dimensional partial differential equation model
  • 本地全文:下载
  • 作者:Yinyin Liu
  • 期刊名称:International Journal of Advances in Engineering and Management
  • 电子版ISSN:2395-5252
  • 出版年度:2021
  • 卷号:3
  • 期号:10
  • 页码:1266-1272
  • DOI:10.35629/5252-031010471049
  • 语种:English
  • 出版社:IJAEM JOURNAL
  • 摘要:In this paper, the one-dimensional PDE model is extended to the two-dimensional model, so that the COVID-19 prediction model which is in line with the actual two-dimensional regional distribution can be established. Based on the prediction model, the undetermined parameters in the differential equation model are inversed by using the spontaneous perturbation stochastic gradient algorithm (SPSA) according to the actual number of infections, so as to accurately predict the number of infections in the future. The effectiveness of this model is also confirmed by the recent outbreak of local epidemic data in China.
  • 关键词:COVID-19prediction;partial differential equation;spontaneous perturbation stochastic gradient algorithm
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