METHODOLOGY FOR DEVELOPING INFORMATION TECHNOLOGY FOR SECURITY-ORIENTED MANAGEMENT OF SOCIO-ECONOMIC SYSTEMS BASED ON FUZZY LOGIC (Computer systems and information technologies, 2024)
In today's environment, socio-economic systems face increasingly complex challenges associated with high levels of uncertainty, risks, and rapid changes in the external environment. This necessitates the development of effective management methods that can ensure the reliability and flexibility of decision-making. The research is aimed at creating a methodology for the development and application of information technology for security-oriented management based on the principles of fuzzy logic. Fuzzy logic, based on the theory of fuzzy sets developed by Lotfi Zadeh, is a powerful tool for working with incomplete and fuzzy data, allowing to model complex systems and processes where traditional approaches may be ineffective.The paper discusses the peculiarities of using fuzzy logic to create models that take into account possible risks and facilitate informed decision-making even with limited information. The proposed methodology allows to integrate various data sources, process them in real time and provide recommendations for risk management and security of socio-economic systems. The study also describes the structure of the technology, which includes the stages of data collection, fuzzification, fuzzy inference, defuzzification, and decision support. Systems based on fuzzy logic demonstrate high adaptability, resilience to change, and the ability to operate in the face of unpredictable changes.The results of the study confirm that the proposed information technology can be applied in various industries, such as transportation, healthcare, and industry, to improve the safety and efficiency of management decisions. The use of the proposed methodology helps to reduce risks, improve the quality of management and adaptability to changes in external conditions, which are key requirements in modern management.
Keywords: security-oriented management; fuzzy logic; information technology; management systems; uncertainty; adaptability; socio-economic systems