PropertyValue
?:abstract
  • The SEIR is a crucial mathematical model for solving infectious disease prediction and other problems in the field of artificial intelligence It is used to effectively prevent and control infectious diseases by studying the infectious diseases’ propagation speed, spatial range, transmission route, dynamic mechanism and other issues In order to improve the prediction of infectious diseases in a certain area, a SEIR model optimization approach based on differential evolution (DE) algorithm is proposed in this paper In this method, the differential evolution is used to optimization the related variables in the model The overall prediction of the adjusted and optimized SEIR model algorithm is conformed to the regional development laws The experimental results show that the SEIR infectious disease model optimized by DE algorithm is accurate and reliable in the analysis of COVID-19 propagation situation, and the model can be used to provide certain theoretical methods and technical support for future outbreak policy formulation © 2020, Springer Nature Switzerland AG
is ?:annotates of
?:creator
?:journal
  • Lect._Notes_Comput._Sci.
?:license
  • unk
?:publication_isRelatedTo_Disease
?:source
  • WHO
?:title
  • A SEIR Model Optimization Using the Differential Evolution
?:type
?:who_covidence_id
  • #969895
?:year
  • 2020

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