Generative artificial intelligence for distributed learning to enhance smart grid communication

Generative artificial intelligence for distributed learning to enhance smart grid communication

Machine learning models are the backbone of smart grid optimization, but their effectiveness hinges on access to vast amounts of training data. However, smart grids face critical communication bottlenecks due to the ever-increasing volume of data from distributed sensors. This paper introduces a nov...

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Bibliographic Details
Main Authors: Seyed Mahmoud Sajjadi Mohammadabadi, Mahmoudreza Entezami, Aidin Karimi Moghaddam, Mansour Orangian, Shayan Nejadshamsi
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-01-01
Series:International Journal of Intelligent Networks
Subjects:
Energy forecasting
Generative AI
Smart grid
Communication efficiency
Distributed training
LSTM
Online Access:http://www.sciencedirect.com/science/article/pii/S2666603024000265
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http://www.sciencedirect.com/science/article/pii/S2666603024000265

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