Modeling of Russian–Ukrainian war based on fuzzy cognitive map with genetic tuning

Alexander Rotshtein, Brian A Polin, Denys I Katielnikov and Neskorodieva Tetiana

The Journal of Defense Modeling and Simulation, 2024, vol. 21, issue 4, 381-394

Abstract: The Russian–Ukrainian conflict is considered as a dynamic system, whose variables are factors affecting the losses of the Russian army and the threat of the use of nuclear weapons. A fuzzy cognitive map (FCM) is used for modeling, that is, a directed graph whose vertices are model variables, and the weights of arcs are the degrees of positive and negative influences of variables on each other. The following factors influencing the losses of the Russian army and the threat of a nuclear strike were selected: resistance of the Ukrainian army, support of Ukraine with weapons, economic sanctions against Russia, opposition to the Russian government and its self-preservation instinct. The degrees of the influence of factors on each other and on the possibility of using nuclear weapons are evaluated by experts using fuzzy terms, which correspond to numeric values. To adjust the FCM, a genetic algorithm is used to select the degrees of influence of factors that minimize the discrepancy between the simulation results and expert estimations. The obtained FCM is used for scenario modeling of the conflict according to the “what if†scheme and ranking of factors according to their degree of influence on the level of nuclear threat.

Keywords: Russian–Ukrainian conflict; modeling; fuzzy cognitive map; genetic algorithm; scenario modeling; nuclear threat; ranking of influencing factors; pair effects (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:joudef:v:21:y:2024:i:4:p:381-394

DOI: 10.1177/15485129231184900

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