Situational centers and decision-making systems. Innovative technologies of national security

Abstract

The article considers modern approaches to the organization and functioning of situational centers (SC). Particular attention is paid to the architecture and components of SC, data collection and processing technologies, as well as the use of machine learning and artificial intelligence (AI) in decision support systems. Data collection and processing technologies play a critical role in the operation of situational centers. The article considers modern approaches to data collection, including the use of satellite images and other sensors. Machine learning and AI are becoming an integral part of decision support systems in situational centers. Chatbots and virtual assistants are also becoming important tools in them, providing automation of interaction with users and decision support. Examples of their application for consultations, monitoring, and rapid response to incidents are described. The development of fundamentally new approaches to creating AI systems is one of the central topics of the article. Multi-connected, multidimensional, receptor-effector neural-like growing networks (mmren-GNs) are considered a promising technology superior to traditional machine learning methods. The article describes the unique capabilities of mmren-GN, including adaptability, self-organization, and efficiency of real-time information processing, and discusses the potential benefits of integrating and using mmren-GN in situational centers. The advantages and disadvantages of traditional machine learning and AI methods are analyzed in comparison with mmren-GN. The importance of these benefits for government and military SCs, especially in military confrontation conditions, is emphasized. Advantages and disadvantages of traditional machine learning and AI methods compared to mmren-GN are analyzed. The authors of the article believe that for the final verification of the effectiveness and potential of mmren-GN, it is necessary to create a prototype of an intelligent system similar to a biological brain. In conclusion, the authors emphasize that mmren-GN opens new horizons in the field of intelligent systems, providing powerful tools for processing, analyzing, and classifying information presented in multidimensional dimensions.