Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Approach
Accurate load forecasting is of vital importance for improving the energy utilization efficiency and economic profitability of intelligent buildings. However, load forecasting is restricted in the popularization and application of conventional load forecasting techniques due to the great difficulty...
Saved in:
Main Authors: | Lanqian Yang, Jinmin Guo, Huili Tian, Min Liu, Chang Huang, Yang Cai |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Buildings |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-5309/15/2/298 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
TDCN: A novel temporal depthwise convolutional network for short-term load forecasting
by: Mingping Liu, et al.
Published: (2025-04-01) -
A power load forecasting method using cosine similarity and a graph convolutional network
by: JI Shan, et al.
Published: (2025-01-01) -
MCADFusion: a novel multi-scale convolutional attention decomposition method for enhanced infrared and visible light image fusion
by: Wangwei Zhang, et al.
Published: (2024-08-01) -
Multi-Sensor Information Fusion with Multi-Scale Adaptive Graph Convolutional Networks for Abnormal Vibration Diagnosis of Rolling Mill
by: Rongrong Peng, et al.
Published: (2025-01-01) -
DPSTCN: Dynamic Pattern-Aware Spatio-Temporal Convolutional Networks for Traffic Flow Forecasting
by: Zeping Dou, et al.
Published: (2024-12-01)