Decentralized asynchronous adaptive federated learning algorithm for securely prediction of distributed power data

Decentralized asynchronous adaptive federated learning algorithm for securely prediction of distributed power data

Introduction: Improving the precision and real-time speed of electricity data prediction while safeguarding data privacy and security holds immense significance for all power system participants’ decision-making. To surmount the issues of exorbitant computational expenses and privacy breaches of tra...

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Bibliographic Details
Main Authors: Qiang Li, Di Liu, Hui Cao, Xiao Liao, Xuanda Lai, Wei Cui
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Energy Research
Subjects:
time-series data prediction
distributed learning
federated learning
decentralization
privacy preservation
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2023.1340639/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2023.1340639/full

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