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On self-adaptive 5G network slice QoS management system: a deep reinforcement learning approach
Sheng Tzong Cheng
, Chang Yu He
, Ya Jin Lyu
, Der Jiunn Deng
Department of Computer Science and Information Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Citations (Scopus)
Overview
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Dive into the research topics of 'On self-adaptive 5G network slice QoS management system: a deep reinforcement learning approach'. Together they form a unique fingerprint.
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Computer Science
Deep Reinforcement Learning
100%
Quality of Service
100%
5G Mobile Communication
100%
Learning Approach
100%
Service Management
100%
User Behavior
33%
Service-Level Agreement
33%
Network Usage
33%
Network Architecture
16%
Network Resource
16%
Computing Resource
16%
Mobile Network
16%
Network Simulator
16%
Network Application
16%
Utilization Rate
16%
Network Slicing
16%
Engineering
Reinforcement Learning
100%
Learning Approach
100%
Quality of Service
100%
5G Mobile Communication
100%
Service Level
33%
Core Network
33%
Communication Network
16%
Network Application
16%
Keyphrases
5G Network Slice
100%
Quality of Service Management
100%