Recommendation ITU-T Y.3116 (02/2022) Traffic typization IMT-2020 management based on an artificial intelligence approach
Summary
History
FOREWORD
Table of Contents
1 Scope
2 References
3 Definitions
     3.1 Terms defined elsewhere
4 Abbreviations and acronyms
5 Conventions
6 Background and motivation
7 Introduction
8 An overview of ML technologies for monitoring and detection of network flows
     8.1 Supervised learning
     8.2 Unsupervised learning
     8.3 Reinforcement learning
     8.4 Semi-supervised learning
9 Traffic typization and recognition for management in IMT-2020 based on the metadata approach and ML
     9.1 Input data for analytical (ML) application
     9.2 Machine learning data model preparation
     9.3 Machine learning data model for neural network training
     9.4 Requirements of neural network architecture for traffic typization and recognition
10 Security consideration
Bibliography
<\pre>