Intelligent Risk Analysis using the example of the COVID-19 Epidemic

Sokolov, A., Royzenzon, G.V., Komendantova, N. ORCID: https://orcid.org/0000-0003-2568-6179, & Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889 (2022). Intelligent Risk Analysis using the example of the COVID-19 Epidemic. In: Twentieth National Conference on Artificial Intelligence with International Participation. pp. 322-334 MPEI.

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Abstract

The paper proposes a scheme for constructing a unified multidimensional classification of methods for intelligent risk analysis. The model approach to risk analysis uses balanced identification technology. This technology served as the basis for creating a system for monitoring and forecasting the state of hazardous phenomena and objects. A practical example of using the proposed approach to predict the development of the Covid-19 epidemic in Moscow (from March 2020 to September 2022) is considered. It is shown how the discrepancy between the forecast and reality leads (after critical analysis) to modification of the model or revision of the accepted scenario of external influence. The prospects for the development of new methods of intelligent risk analysis are critically analyzed.

Item Type:	Book Section
Uncontrolled Keywords:	MODELING , BALANCED IDENTIFICATION , RISK MANAGEMENT , ARTIFICIAL INTELLIGENCE
Research Programs:	Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT)
Depositing User:	Luke Kirwan
Date Deposited:	06 Nov 2023 09:45
Last Modified:	07 Dec 2023 11:02
URI:	https://pure.iiasa.ac.at/19166

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