Akademik Məlumat İdarəetmə Sistemi
7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, İstanbul, Turkey, 29 - 31 July 2025, vol.1531 LNNS, pp.808-815, (Full Text)
The rapid advancement of communication technologies necessitates innovative approaches to address the complexities of modern interconnected systems. Traditional methods often struggle with imprecision and uncertainty, limiting adaptability and efficiency. This paper explores the integration of fuzzy logic with human-centric artificial intelligence (AI) and autonomous network intelligence to enhance decision-making, resource management, and user experience in next-generation communication systems. Fuzzy logic, with its ability to handle degrees of truth, enables more adaptive, intuitive, and context-aware decision-making processes compared to conventional binary logic. By embedding fuzzy reasoning into AI-driven networks, communication infrastructures can achieve real-time optimization, seamless connectivity, and intelligent resource allocation under dynamic conditions. Using MATLAB's Fuzzy Inference System (FIS), we model key parameters such as user experience, network load, resource availability, and decision confidence to optimize system performance. Our results demonstrate that fuzzy logic significantly enhances adaptability, efficiency, and user-centricity in communication networks. This study highlights the transformative potential of fuzzy logic in autonomous AI-driven communication systems and lays the foundation for future research in hybrid AI models, deep learning integration, and sustainable network management for next-generation technologies.