Comparing Long Short-Term Memory (LSTM) and bidirectional LSTM deep neural networks for power consumption prediction

Comparing Long Short-Term Memory (LSTM) and bidirectional LSTM deep neural networks for power consumption prediction

Electric consumption prediction methods are investigated for many reasons, such as decision-making related to energy efficiency as well as for anticipating demand and the dynamics of the energy market. The objective of the present work is to compare two Deep Learning models, namely the Long Short-Te...

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Bibliographic Details
Main Authors: Davi Guimarães da Silva, Anderson Alvarenga de Moura Meneses
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Energy Reports
Subjects:
Electric consumption forecast
Deep learning
Univariate time series
Deep neural networks
Long-Short Term Memory
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723014208

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http://www.sciencedirect.com/science/article/pii/S2352484723014208

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