Mathematical Models, Algorithms and Software Package for the National Security State of Russia

Yandybaeva, N. V.; Rezchikov, A. F.; Kushnikov, V. A.; Ivaschenko, Vladimir; Kushnikov, O. V.; Tsvirkun, Anatoly

doi:10.1007/978-3-030-12072-6_52

Cited by 5 publications

(1 citation statement)

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“…Therefore, a new approach is used to solve the problem. Based on the decomposition of separate key factors in the current conditions, it allows us to obtain the required solution [41,42].…”

Section: Applications Of Kolmogorov-chapman Equationsmentioning

confidence: 99%

Methodology for Assessing the Risks of Regional Competitiveness Based on the Kolmogorov–Chapman Equations

Chernyshova,

Veshneva,

Firsova

et al. 2023

Mathematics

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The relevance of research on competitiveness at the meso level is related to the contemporary views of a region as an essential element of the economic space. The development of forecasting and analytical methods at the regional level of the economy is a key task in the process of strategic decision making. This article proposes a method of quantitative assessment of the risks of regional competitiveness. The novelty of this approach is based on both a fixed-point risk assessment and scenario-based predictive analysis. A hierarchical structure of indicators of competitiveness of regions is offered. A method based on the Kolmogorov–Chapman equations was used for the predictive estimation of risks of regional competitiveness. The integrated risk assessment is performed using the modified fuzzy ELECTRE II method. A web application has been implemented to assess the risks of competitiveness of Russian regions. The functionality of this application provides the use of multi-criteria decision-making methods based on a fuzzy logic approach to estimate risks at a specified time, calculating the probability of risk events and their combinations in the following periods and visualizing the results. Approbation of the technique was carried out for 78 Russian regions for various scenarios. The analysis of the results obtained provides an opportunity to identify the riskiest factors of regional competitiveness and to distinguish regions with different risk levels.

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“…Therefore, a new approach is used to solve the problem. Based on the decomposition of separate key factors in the current conditions, it allows us to obtain the required solution [41,42].…”

Section: Applications Of Kolmogorov-chapman Equationsmentioning

confidence: 99%