ADAPTATION OF THE DECISION-MAKING PROCESS IN THE MANAGEMENT OF CRITICAL INFRASTRUCTURE

Abstract

Context. The problem of human factor management in the process of making relevant decisions in the management of critical infrastructure facilities is currently very important and complex. This issue is becoming increasingly significant due to the dynamic and unpredictable nature of the environment in which these facilities operate. Effective management of CIF requires the development of new models and methods that are based on adaptive management principles. These models and methods must take into account the personal emotional and cognitive capabilities of the decision maker, who is often operating under the influence of destabilizing uncertain factors. The challenge is further compounded by the need to integrate these adaptive methods into existing human-machine systems, ensuring that they can respond in real-time to the rapidly changing conditions that can affect the decision-making process. The complexity and importance of this problem necessitate a multifaceted approach that combines probabilistic methods, intellectual technologies, and information-cognitive technologies. These technologies must be capable of providing real-time adaptation and assessment of the DM’s emotional and cognitive state, which is critical for making relevant and timely decisions. The current unresolved problems in the field of creating adaptive information technologies for decision support in the management of CIF highlight the urgent need for a promising approach that can address these issues effectively and efficiently.

Objective. The objective is to propose a a comprehensive method for evaluating the process of relevant decision-making, which depends on the functional stability of critical infrastructure facilities and the adaptation of factors related to the emotional-cognitive state of the decision maker. This method aims to provide a systematic approach to understanding how various factors, including the psycho-functional state of the DM, influence the decision-making process. Additionally, the objective includes the development of adaptive information and intellectual technologies that can support real-time evaluation and adjustment of the DM’s emotional and cognitive states. This approach seeks to ensure that decisions are made efficiently and effectively, even under the influence of destabilizing uncertain factors. By addressing these aspects, the method aims to enhance the overall reliability and resilience of the CIF
management processes. Furthermore, the objective encompasses the integration of Bayesian networks and a comprehensive knowledge base to facilitate the decision support system in providing timely and accurate information for decision-making.

Method. To implement this method, probabilistic methods, intellectual and information-cognitive technologies were used to provide acceptable adaptation and evaluation of the relevant decision-making process in real-time.

Results. The proposed method, based on intellectual and information-cognitive technology, allows for real-time assessment and adaptation of the emotional and cognitive state of the decision maker during the process of making relevant decisions. The implementation of probabilistic methods and Bayesian networks has enabled the development of a robust decision support system that effectively integrates adaptive management principles. This system ensures that the decision-making process remains stable and reliable, even in the presence of destabilizing uncertain factors. The real-time capabilities of the system allow for prompt adjustments to the psycho-functional state of the DM, which is critical for maintaining the functional stability of critical infrastructure facilities. The results demonstrate that the use of intellectual technologies and a comprehensive knowledge base significantly enhances the DM’s ability to make informed decisions. Experiments have shown that this method improves the overall efficiency and effectiveness of CIF management, providing a promising approach for future applications in adaptive decision support processes. The results obtained from these experiments validate the potential of the proposed method to revolutionize the management of CIF by ensuring that decisions are both timely and appropriate, thereby contributing to the resilience and reliability of these essential facilities..

Conclusions. The results of the experiments allow us to recommend the use of the proposed method of rapid assessment and adaptation of the emotional and cognitive state of the decision maker for the process of making relevant decisions in real-time. The integration of intellectual and information-cognitive technologies into the decision support system has proven to be effective in enhancing the stability and reliability of the decision-making process in the management of critical infrastructure facilities. The realtime capabilities of the system facilitate prompt adjustments to the psycho-functional state of the DM, ensuring that decisions are made efficiently and effectively, even under the influence of destabilizing uncertain factors. The experimental results demonstrate that the proposed method significantly improves the overall efficiency of CIF management by providing a robust framework for adaptive decision support. The results obtained can be used in the development of adaptive DSS in the management of CIF, offering a promising approach for future applications. This method not only enhances the decision-making capabilities of DMs but also contributes to the resilience and reliability of CIF, ensuring their functional stability in dynamic and uncertain environments.