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JOURNALS // Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya // Archive

Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 2020 Volume 16, Issue 3, Pages 249–259 (Mi vspui455)

This article is cited in 4 papers

Computer science

Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach

V. V. Zakharov, Yu. E. Balykina

St. Petersburg State University, 7-9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation

Abstract: 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 short-term 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.

Keywords: modeling, forecasting, COVID-19 epidemic, percentage rate of increase, case-based reasoning, heuristic.

UDC: 519, 616-036.22

MSC: 62P10

Received: July 20, 2020
Accepted: August 13, 2020

DOI: 10.21638/11701/spbu10.2020.303



© Steklov Math. Inst. of RAS, 2024