TCN-QRNN model for short term energy consumption forecasting with increased accuracy and optimized computational efficiency

TCN-QRNN model for short term energy consumption forecasting with increased accuracy and optimized computational efficiency

Abstract In the context of the growing volume and complexity of data, traditional methods of energy consumption forecasting, such as Recurrent Neural Networks (RNN), face computational complexity issues that limit their real-time application. This also complicates the effective management of energy...

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Bibliographic Details
Main Authors: Lesia Mochurad, Roman Levkovych
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Time series forecasting
Neural network optimization
Model efficiency
Parallel processing
Resource-constrained environments
Online Access:https://doi.org/10.1038/s41598-025-14423-z
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https://doi.org/10.1038/s41598-025-14423-z

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