No abstract

Statement of a problem. The increasing complexity in high-tech systems leads to potentially disastrous failure models and new kinds of safety issues. This led to the development of new approaches, for modeling accidents and risk management. In recent years, extended and hybrid approaches have been gaining popularity due to their effectiveness in decision-making for the design and operation of socio-technical systems. The proliferation of these approaches makes it difficult to select the appropriate approach for a particular system. Purpose. Conduct a comparative analysis of various hybrid approaches of accidents in complex systems, identify the strengths and weaknesses of each one, and study the feasibility of their use in risk management in socio-technical systems. Results. The paper analyzes the main approaches of accident modeling (FRAM, STAMP, failure tree, AcciMap) and their limitations in determining cause-effect relationships and dynamics of modern complex systems. New approaches to safety and accident modeling in sociotechnical systems are discussed, these approaches depend on combining several models into one hybrid approach: FuzzyFTA, FRAM-ANP, ACAT-FRAM, STAMP-HFACS, AcciMap-ANP, and SD-ET-FT-ANN. A review of hybrid approaches of accident modeling in complex systems and identify weaknesses and strengths, as well as the application field of each one of these approaches. Practical importance. This study will be a guide for researchers in the field of accident modeling and risk management in sociotechnical systems. It also concludes that it is necessary to use different approaches to risk management depending on the type of risk and the complexity of the system.

Statement of a problem. One of the main tasks today is to prevent accidents in complex systems, which requires determining their cause. In this regard, several theories and models of the causality of accidents are being developed. Traditional approaches to accident modeling are not sufficient for the analysis of accidents occurring in complex environments such as socio-technical systems, since an accident is not the result of individual component failure or human error. Therefore, we need more systematic methods for the investigation and modeling of accidents. Purpose. Conduct a comparative analysis of accident models in complex systems, identify the strengths and weaknesses of each of these models, and study the feasibility of their use in risk management in socio-technical systems. The paper analyzes the main approaches of accident modeling and their limitations in determining the cause-and-effect relationships and dynamics of modern complex systems. the methodologies to safety and accident models in sociotechnical systems based on systems theory are discussed. The complexity of sociotechnical systems requires new methodologies for modeling the development of emergency management. At the same time, it is necessary to take into account the socio-technical system as a whole and to focus on the simultaneous consideration of the social and technical aspects of the systems. When modeling accidents, it is necessary to take into account the social structures and processes of social interaction, the cultural environment, individual characteristics of a person, such as their abilities and motivation, as well as the engineering design and technical aspects of systems. Practical importance. Based on analyzing various techniques for modeling accidents, as well as studying the examples used in modeling several previous accidents and review the results of this modeling, it is concluded that it is necessary to improve the modeling techniques. The result was the appearance of hybrid models of risk management in socio-technical systems, which we will consider in detail in our next work.

No abstract

Under "Industry 4.0" conditions, the automatic prediction of emergence and evolution of innovative technologies is an important challenge. To solve this problem, a hybrid approach to big data streams analysis is proposed and developed. This approach allows the automated monitoring and forecasting of situations development through processing streams of heterogeneous data which is presented, in particular, by text documents, time series and database records. The proposed approach includes detecting events in data streams, forming situations, identifying possible scenarios for their further development and preparing suggestions for decision makers. To represent events that are reflected in a stream of structured data, a frame-based model is proposed. To form situational chains that reflect the development of innovative technologies, an incremental clustering method is used. Forecasting further evolution of the analyzed innovative technology consists in forming possible scenarios for the situation's development based on the case-based approach. An example of an event and a situation detected in a stream of structured data, as well as an example of a scenario generated for the detected situation are presented.