Fuzzy cognitive maps in reliability analysis of complex human-machine systems: Theore-tical and applied aspect

The aim of the study is to analyze the applicability of fuzzy cognitive maps (FCM) to analyze the reliability of complex human-machine systems (HMS), as well as to develop algorithms for evaluating factors influencing the reliability of the system, taking into account expert assessments. The paper highlights the limitations of classical probabilistic and regression methods, which are difficult to apply to HMS due to the interdependence of qualitative assessments, as well as the need to take into account the presence of a human factor. As an alternative solution, the use of fuzzy cognitive maps is considered, which provides the possibility of representing the dynamics of the system in the form of an oriented weighted graph, where the vertices are key concepts, and the arcs are cause–and-effect relationships evaluated by experts. Using the example of an analysis of the reliability of an intelligent video monitoring system of a protected object, the construction of a fuzzy cognitive map is demonstrated, an algorithm for calculating importance indices and coefficients of the combined influence of factors is given to determine the integral indicator of the reliability of the system. A computational algorithm has been developed, and the results of its software implementation are presented. The factors that have the greatest impact on the target variable are highlighted. The prospects of using graph knowledge bases for organizing the collection and storage of information forming cognitive fuzzy maps are noted. The advantages of the considered approach include the possibility of using the method when working with expert information, the integration of heterogeneous factors within a single model, its adaptability and scalability.