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A Variational Autoencoder-Based Dimensionality Reduction Technique for Generation Forecasting in Cyber-Physical Smart Grids

conference contribution

posted on 2021-01-01, 00:00 authored by Devinder KaurDevinder Kaur, Shama IslamShama Islam, Apel MahmudApel Mahmud

A Variational Autoencoder-Based Dimensionality Reduction Technique for Generation Forecasting in Cyber-Physical Smart Grids

History

Event

Communications. Conference (2021 : Montreal, Quebec)

Pagination

1 - 6

Publisher

IEEE

Location

Montreal, Quebec

Place of publication

Piscataway, N.J.

Publisher DOI

https://doi.org/10.1109/ICCWorkshops50388.2021.9473748

Start date

2021-06-14

End date

2021-06-23

ISBN-13

9781728194417

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

ICC 2021 : Proceedings of the IEEE International Conference on Communications

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A Variational Autoencoder-Based Dimensionality Reduction Technique for Generation Forecasting in Cyber-Physical Smart Grids

Research Publications

Categories

Electrical and Electronic Engineering not elsewhere classified

Keywords

deep learning Dimensionality reduction energy forecasting posterior approximation renewable energy generation VAE-BiLSTM

Licence

All Rights Reserved

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