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This article is cited in 4 scientific papers (total 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.
Received: July 20, 2020 Accepted: August 13, 2020
Citation:
V. V. Zakharov, Yu. E. Balykina, “Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach”, Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 16:3 (2020), 249–259
Linking options:
https://www.mathnet.ru/eng/vspui455 https://www.mathnet.ru/eng/vspui/v16/i3/p249
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Abstract page: | 95 | Full-text PDF : | 20 | References: | 24 | First page: | 5 |
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