Time series prediction based on LSTM-attention-LSTM model

Time series forecasting uses data from the past periods of time to predict future information, which is of great significance in many applications. Existing time series forecasting methods still have problems such as low accuracy when dealing with some non-stationary multivariate time series data fo...

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Veröffentlicht in:	IEEE access Jg. 11; S. 1
Hauptverfasser:	Wen, Xianyun, Li, Weibang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	attention mechanisms Autoregressive processes Coders Data models Decoding encoder and decoder model Forecasting Logic gates long short-term memory networks Mathematical models Multivariate analysis Predictive models Sequences Time series Time series analysis Time series forecasting
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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