New Forecasting Metrics Evaluated in Prophet, Random Forest, and Long Short-Term Memory Models for Load Forecasting

Data mining is vital for smart grids because it enhances overall grid efficiency, enabling the analysis of large volumes of data, the optimization of energy distribution, the identification of patterns, and demand forecasting. Several performance metrics, such as the MAPE and RMSE, have been created...

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Hlavní autoři:	Prajowal Manandhar, Hasan Rafiq, Edwin Rodriguez-Ubinas, Themis Palpanas
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-12-01
Edice:	Energies
Témata:	smart grid load forecasting machine learning deep learning time series performance metrics
On-line přístup:	https://www.mdpi.com/1996-1073/17/23/6131
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