Prioritization of measures to reduce the risks of man-made emergencies taking into account the contribution of scenarios to overall uncertainty
DOI:
https://doi.org/10.33408/2519-237X.2025.9-4.517Keywords:
safety, emergency situations, risk management, entropy analysis, risk assessment, man-made disasters, uncertainty analysis, accident preventionAbstract
Purpose. Development of a quantitative measure of the contribution of emergency scenarios to the overall uncertainty of the risk of man-made emergencies at fuel and energy facilities, based on the entropy of the system, the informational significance of individual scenarios and the degree of effectiveness of protective measures. This will allow for the consideration of low-probability but high-informational scenarios and ensure a rational choice of measures within a limited budget.
Methods. The primary method utilizes an information-entropy approach, allowing for a quantitative assessment of the contribution of each emergency scenario to the overall uncertainty of the system. An optimization model for selecting protective measures is constructed, taking into account their effectiveness, cost, and the informational significance of the scenarios. A numerical experiment is conducted to evaluate the effectiveness of the proposed approach under conditions of limited budgets and multiple risks.
Findings. The study's results demonstrated that using the informational significance of scenarios enables the development of more effective resource allocation strategies. The proposed model reduces residual risk at a lower cost compared to classical approaches. A numerical experiment confirmed the method's applicability for the informed selection of protective measures under conditions of high uncertainty and limited budgets for preventing man-made emergencies.
Application field of research. The developed model can be applied to risk management systems at industrial and infrastructure facilities exposed to man-made emergencies. The approach is relevant for designing civil defense action plans, justifying safety investments, and developing digital decision support platforms in resource-constrained environments with high uncertainty.
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