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TCN-MLP: A Hybrid Model for Short-Term Electrical Load Fore..:
, In:
2023 Intelligent Methods, Systems, and Applications (IMSA)
,
Farid, Karim S.
;
Ali, A. A.
;
Salem, Sameh A.
. - p. 533-538 , 2023
Link:
https://doi.org/10.1109/IMSA58542.2023.10217765
RT T1 <cTitle>2023 Intelligent Methods, Systems, and Applications (IMSA)</cTitle>: T1 <Title>TCN-MLP: A Hybrid Model for Short-Term Electrical Load Forecasting</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10217765&Exemplar=1&LAN=DE A1 Farid, Karim S. A1 Ali, A. A. A1 Salem, Sameh A. A1 Mohamed, Amr E. YR 2023 K1 Analytical models K1 Load forecasting K1 Time series analysis K1 Predictive models K1 Data models K1 Hybrid power systems K1 Convolutional neural networks K1 Short-Term Load Forecasting (STLF) K1 Integrated Moving Average (ARIMA) K1 Extreme Gradient boosting (XBoost) K1 Prophet K1 Multilayer Perceptron (MLP) K1 Autoregressive Temporal Convolutional Networks (TCN)k SP 533 OP 538 LK http://dx.doi.org/https://doi.org/10.1109/IMSA58542.2023.10217765 DO https://doi.org/10.1109/IMSA58542.2023.10217765 SF ELIB - SuUB Bremen
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