Akademik Veri Yönetim Sistemi
5th International Conference on Electrical, Computer and Energy Technologies (ICECET), Paris, Fransa, 3 - 06 Temmuz 2025, ss.3009-3014, (Tam Metin Bildiri)
In parallel with technological developments, mobile and wireless communication technologies are advancing rapidly. Today, 5G technology is widely used, while studies on 6G continue. As a result of these developments, the use of internetconnected devices is increasing both in daily life and in industrial areas. This increase in the number of devices brings critical requirements such as additional resources and energy consumption in networks, communication prioritization, and reliable data transmission. In response to these needs, 6G technology offers dynamic, flexible, a nd s cenario-based r esource a llocation based on network slicing. Network slicing makes it possible to support innovative services such as super-eMBB, massive-MTC, and super-URLLC. In this paper, PSO-based feature selection and ensemble learning methods are used to solve the network slicing classification p roblem i n 6 G n etworks. I n a ddition, t he LIME method is applied to help better interpret model predictions and make reliable decisions. The main objective of this study is to contribute to the development of autonomous and seamless network systems that are suitable for the dynamic and complex nature of 6G. Thus, it aims to create reliable, flexible, a nd e fficient ne twork solutions by making the best use of the innovations offered by 6G.