… network strategy generation based on knowledge and intelligent anomaly detection based on
knowledge for realizing 6G … 学习和强 化学习(RL, reinforcement learning)等.资源管控 的差异…

… His research interest covers 5G/6G network architecture, cloud computing and virtualization,
… Deep reinforcement learning for stochastic computation offloading in digital twin networks. …

… Machine learning in wireless sensor networks: algorithms, … Outlier detection techniques
for wireless sensor networks: a … Machine learning based intelligent cognitive network using …

… intelligence)技术 能够更好地支撑6G 的智能化需求.其中,基于深 度神经网络(DNN, deep neural
network)的深度学 习(DL, deep learning… anomaly detection generative adversarial network)…

… anomaly detection benchmark algorithm. Key words: AIOps, … 6G 网络的部署,分析网 络中
的数据并学习其经验和规则可用于优化网络 管理,这促使智能运维(AIOps, artificial intelligence …

… traditional network traffic anomaly detection methods only … use of multi-scale feature
information, which may lead to low accuracy of anomaly detection results, a network traffic anomaly …

… the network” according to “What to do”, which got network knowledge through joint optimization
of machine learning … , network information measurement, network policy generation, and …

… Introduction of unsupervised learning methods in deep learning[J]. Computer Systems &
Applica… From MIM-based GAN to anomaly detection: event probability influence on generative …

… Adversarial Networks (GAN) training and significantly improving anomaly detection performance.
At the … On the feasibility of deep learning in sensor network intrusion detection[J]. IEEE …

… This technique enjoys advantages such as a large penetration rate (~50% urban population
… Anomaly detection on attributed networks via contrastive self-supervised learning. IEEE …