Analysis of Machine Learning Models for Remote Diagnostics of Network Elements

Omonov, Ibratbek, Bekimetov, Alisher

Al-Farg'oniy avlodlari · 2025-yil

Annotatsiya

Telecommunication networks possess a complex architecture consisting of various devices, transmission lines, and control systems. Failures or interruptions in the operation of network elements can lead to the malfunction of the entire system. Therefore, it is essential to develop remote diagnostic systems and apply Machine Learning (ML) models for predictive diagnostics. Network elements represent an integral part of the digital infrastructure. Networks based on technologies such as Wi-Fi, 5G, Bluetooth, ZigBee, NB-IoT, and others serve as the primary means of data transmission across various sectors - industry, transportation, healthcare, and the Internet of Things (IoT). 

Maqola ma’lumotlari
MualliflarOmonov, Ibratbek, Bekimetov, Alisher
JurnalAl-Farg'oniy avlodlari
Nashr sanasi2025-11-16
Son4
Betlar3-7
TilRus

Kalit so‘zlar

сеть, элементы сети, диагностика, машинное обучение, дистанционная диагностика, реальное время., Tarmoq, tarmoq elementlari, diagnostika, machine learning, masofaviy diagnostika, real vaqt., Network, network elements, diagnostics, machine learning, remote diagnostics, real-time

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