Comparative study of long short-term memory (LSTM), bidirectional LSTM, and traditional machine learning approaches for energy consumption prediction

Comparative study of long short-term memory (LSTM), bidirectional LSTM, and traditional machine learning approaches for energy consumption prediction

Responsible, efficient, and environmentally conscious energy consumption practices are increasingly essential for ensuring the reliability of the modern electricity grid. This study focuses on leveraging time series analysis to improve forecasting accuracy, crucial for various application domains wh...

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Bibliographic Details
Main Authors: Hamed Alizadegan, Behzad Rashidi Malki, Arian Radmehr, Hossein Karimi, Mohsen Asghari Ilani
Format: Article
Language:English
Published: SAGE Publishing 2025-01-01
Series:Energy Exploration & Exploitation
Online Access:https://doi.org/10.1177/01445987241269496
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https://doi.org/10.1177/01445987241269496

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