has been cited by the following article(s):
[1]
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A two-layer SSA-XGBoost-MLR continuous multi-day peak load forecasting method based on hybrid aggregated two-phase decomposition
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.09.008
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[2]
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A two-layer SSA-XGBoost-MLR continuous multi-day peak load forecasting method based on hybrid aggregated two-phase decomposition
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.09.008
|
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[3]
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A two-layer SSA-XGBoost-MLR continuous multi-day peak load forecasting method based on hybrid aggregated two-phase decomposition
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.09.008
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[4]
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Deep Learning for Daily Peak Load Forecasting–A Novel Gated Recurrent Neural Network Combining Dynamic Time Warping
IEEE Access,
2019
DOI:10.1109/ACCESS.2019.2895604
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