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1 Ergebnisse
1
Multi-step-ahead time series forecasting based on CEEMDAN d..:
, In:
2022 International Conference on Advanced Computing and Analytics (ACOMPA)
,
Minh, Ha Binh
;
An, Nguyen Hoang
;
Tuan, Nguyen Minh
- p. 54-59 , 2022
Link:
https://doi.org/10.1109/ACOMPA57018.2022.00015
RT T1 <cTitle>2022 International Conference on Advanced Computing and Analytics (ACOMPA)</cTitle>: T1 <Title>Multi-step-ahead time series forecasting based on CEEMDAN decomposition and temporal convolutional networks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10005585&Exemplar=1&LAN=DE A1 Minh, Ha Binh A1 An, Nguyen Hoang A1 Tuan, Nguyen Minh YR 2022 K1 Computational modeling K1 Time series analysis K1 Predictive models K1 Data models K1 Reliability K1 Forecasting K1 Stock markets K1 multi-step-ahead forecasting K1 time series prediction K1 CEEMDAN decompositon K1 temporal convolutional networks SP 54 OP 59 LK http://dx.doi.org/https://doi.org/10.1109/ACOMPA57018.2022.00015 DO https://doi.org/10.1109/ACOMPA57018.2022.00015 SF ELIB - SuUB Bremen
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