Randomized machine learning of nonlinear models with application to forecasting the development of an epidemic process

DOI10.1134/S0005117921060060zbMath1471.93263OpenAlexW3180235386MaRDI QIDQ1982849

Alexey Yu. Popkov

Publication date: 14 September 2021

Published in: Automation and Remote Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0005117921060060

zbMATH Keywords

entropyforecastingrandomized forecastingCOVID-19SARS-CoV-2entropy-based estimationrandomized machine learning

Mathematics Subject Classification ID

Epidemiology (92D30) Learning and adaptive systems in artificial intelligence (68T05) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Uses Software

• PRMLT

Cites Work

• Elements of randomized forecasting and its application to daily electrical load prediction in a regional power system
• Mathematical epidemiology.
• Information Theory and Statistical Mechanics
• Communication Theory of Secrecy Systems*
• Probability Theory
• Learning representations by back-propagating errors
• The elements of statistical learning. Data mining, inference, and prediction
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