Electricity price forecast based on the STL-TCN-NBEATS model

Taking long-term high-frequency electricity price data as the research content, this paper proposes seasonal and trend decomposition using loess-temporal convolutional network-neural basis expansion analysis for an interpretable time series forecasting (STL-TCN-NBEATS) model to solve the problems of...

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Bibliografski detalji

Glavni autori:	Biao Zhang, Chao Song, Xuchu Jiang, Ying Li
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2023-01-01
Serija:	Heliyon
Teme:	STL-TCN-NBEATS Multiple time series forecasting Deep learning Interpretability
Online pristup:	http://www.sciencedirect.com/science/article/pii/S2405844023002360
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