Issues of Adaptive Neuro-Fuzzy Modeling of Operational and Predictive Control Systems for Information Flows in Telecommunication Networks

Nigmatov Zafarjon Zakirovich

Authors

Nigmatov Zafarjon Zakirovich Associate Professor of the Artificial Intelligence, Cybersecurity and Communication Training Cycle Department of Advanced Military Technologies Institute of Ground Forces University of Military Security and Defense of the Republic of Uzbekistan PhD in Technical Sciences, Associate Professor

Keywords:

telecommunication networks, information flows, operational and predictive control, adaptive neuro-fuzzy model, Takagi–Sugeno mechanism, traffic distribution, military communication system

Abstract

This article discusses the issues of improving the efficiency of information flow management in telecommunication networks. In particular, scientific approaches to the development of operational and predictive control systems based on adaptive neuro-fuzzy modeling are analyzed. The proposed models make it possible to reduce computational load in traffic flow distribution, enhance real-time decision-making capabilities, and ensure stable network operation under various uncertainty conditions. Furthermore, the performance of neuro-fuzzy models of different orders is comparatively evaluated, and the mechanisms by which their application in military communication networks reduces information transmission losses and increases network throughput are revealed. The research findings are of significant scientific and practical importance for identifying priority directions in the development of communication systems of the Armed Forces.