A Federated Deep Reinforcement Learning-based Approach to Secure Resource Allocation in Power Communication Networks-Reference-Cited by-同舟云学术

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A Federated Deep Reinforcement Learning-based Approach to Secure Resource Allocation in Power Communication Networks

Published:2022-08 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Artificial Intelligence, Information Processing and Cloud Computing (AIIPCC)
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Author:

Mao ZhengXiong¹,Zhang Hang¹,Li Hui¹,Huang ZuYuan¹,Tian Yuan¹,Zhao XiaoPing¹

Affiliation:

1. Information center of Yunnan Power Grid Co., Ltd,Kunming,China,650011

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10070113/10069879/10070323.pdf?arnumber=10070323

Reference15 articles.

1. Node selection method in federated learning based on deep reinforcement learning[J];wenchen;Journal on Communications,2021

2. Energy and Information Management Strategy Based on Federated Learning for Wireless Network Nodes[J];wenqi;Computer Engineering,2022

3. Optimization Method of Spectrum Resource Allocation in Low Frequency Band of 5g Network[J];yang;Computer Simulation,2020

4. RELIABLE: Resource Allocation Mechanism for 5G Network using Mobile Edge Computing

5. Fractional Rider Deep Long Short Term Memory Network for Workload Prediction-Based Distributed Resource Allocation Using Spark in Cloud Gaming

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