An Ensemble Model of Attention-Enhanced N-BEATS and XGBoost for District Heating Load Forecasting

An Ensemble Model of Attention-Enhanced N-BEATS and XGBoost for District Heating Load Forecasting

Accurate heat load forecasting is essential for the efficiency of District Heating Systems (DHS). Still, it is challenged by the need to model long-term temporal dependencies and nonlinear relationships with weather and other factors. This study proposes a hybrid deep learning framework combining an...

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Bibliographic Details
Main Authors: Shaohua Yu, Xiaole Yang, Hengrui Ye, Daogui Tang, Hamidreza Arasteh, Josep M. Guerrero
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
district heating forecasting
N-BEATS
multi-head self-attention
XGBoost
model ensemble
Online Access:https://www.mdpi.com/1996-1073/18/15/3984
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