Robust Gas Demand Prediction Using Deep Neural Networks: A Data-Driven Approach to Forecasting Under Regulatory Constraints

Robust Gas Demand Prediction Using Deep Neural Networks: A Data-Driven Approach to Forecasting Under Regulatory Constraints

Accurate gas consumption forecasting is critical for modern energy systems due to complex consumer behavior and regulatory requirements. Deep neural networks (DNNs), such as Seq2Seq with attention, TiDE, and Temporal Fusion Transformers, are promising for modeling complex temporal relationships and...

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Bibliographic Details
Main Authors: Kostiantyn Pavlov, Olena Pavlova, Tomasz Wołowiec, Svitlana Slobodian, Andriy Tymchyshak, Tetiana Vlasenko
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
natural gas consumption and demand forecasting
neural networks
Seq2Seq
TiDE
Temporal Fusion Transformer
regulatory restrictions
Online Access:https://www.mdpi.com/1996-1073/18/14/3690
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https://www.mdpi.com/1996-1073/18/14/3690

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