Enhanced Transformer for Multivariate Load Forecasting: Timestamp Embedding and Convolution-Augmented Attention

Aiming at the insufficient capture of temporal dependence and weak coupling of external factors in multivariate load forecasting, this paper proposes a Transformer model integrating timestamp-based positional embedding and convolution-augmented attention. The model enhances temporal modeling capabil...

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Bibliografiske detaljer

Principais autores:	Wanxing Sheng, Xiaoyu Yang, Dongli Jia, Keyan Liu, Zhenhao Wang, Rongheng Lin
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2026-01-01
Serier:	Energies
Fag:	multivariate load forecasting attention mechanism transformers deep learning
Online adgang:	https://www.mdpi.com/1996-1073/19/3/596
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