title: Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach
metadata.name: dc.contributor.author
metadata.value: Zakharov, Victor V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Balykina, Yulia E.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2020-11-19T10:38:46Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2020-11-19T10:38:46Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2020-09
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Zakharov V. V., Balykina Yu. E. Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2020, vol. 16, iss. 3, pp. 249–259.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2020.303
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/20725
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The case-based rate reasoning (CBRR) method is presented for predicting future values of
  the coronavirus epidemic’s main parameters in Russia, which makes it possible to build shortterm forecasts based on analogues of the percentage growth dynamics in other countries. A
  new heuristic method for estimating the duration of the transition process of the percentage
  increase between specified levels is described, taking into account information about the
  dynamics of epidemiological processes in countries of the spreading chain. The CBRR
  software module has been developed in the MATLAB environment, which implements the
  proposed approach and intelligent proprietary algorithms for constructing trajectories of
  predicted epidemic indicators.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 16; Issue 3
metadata.lang: -
metadata.name: dc.subject
metadata.value: modeling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: forecasting
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: COVID-19 epidemic
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: percentage rate of increase
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: casebased reasoning
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: heuristic
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 249-259.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/20725/1/249-259.pdf
resources.format: Adobe PDF
resources.size: 1,04 MB