Multi-scale temporal features extraction based graph convolutional network with attention for multivariate time series prediction

•A novel GCN model is proposed for multivariate time series prediction.•EMD is used to extract multi-scale temporal features of original time series.•Multi-head attention mechanism is utilized to explore the spatial dependencies.•Real datasets from various fields confirms the superiority of the meth...

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Veröffentlicht in:	Expert systems with applications Jg. 200; S. 117011
Hauptverfasser:	Chen, Yawen, Ding, Fengqian, Zhai, Linbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 15.08.2022 Elsevier BV
Schlagworte:	Artificial neural networks Feature extraction Features extraction Forecasting Graph neural network Mathematical models Multi-head attention Multivariate analysis Multivariate time series prediction Neural networks Nodes Prediction models Spatial dependencies Time series Multivariate time series prediction Features extraction Graph neural network Multi-head attention
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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