Cellular fault prediction of graphical representation based on spatio-temporal graph convolutional networks-Reference-Cited by-同舟云学术

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Cellular fault prediction of graphical representation based on spatio-temporal graph convolutional networks

Published:2024-01 Issue: Volume:213 Page:78-87
ISSN:0140-3664
Container-title:Computer Communications
language:en
Short-container-title:Computer Communications

Author:

Qian Bing,Xie Hanlei^ORCID,Wu Wei,Yang Yan

Publisher

Elsevier BV

Subject

Computer Networks and Communications

Reference28 articles.

1. Research and application of AI in 5G network operation and maintenance;Li,2020

2. The disruptions of 5G on data-driven technologies and applications;Loghin;IEEE Trans. Knowl. Data Eng.,2020

3. Telecom big data assisted BS resource analysis for LTE/5G systems;Xu,2019

4. Crowdsourcing or network kpis? a twofold perspective for qoe prediction in cellular networks;Pimpinella,2021

5. Graph neural network based root cause analysis using multivariate time-series KPIs for wireless networks;Yen,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fault Detection in Telecom Networks Using Bi-Level Federated Graph Neural Networks;2023 IEEE International Conference on Data Mining Workshops (ICDMW);2023-12-04

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