Additive Ensemble Neural Network with Constrained Weighted Quantile Loss for Probabilistic Electric-Load Forecasting

Additive Ensemble Neural Network with Constrained Weighted Quantile Loss for Probabilistic Electric-Load Forecasting

This work proposes a quantile regression neural network based on a novel constrained weighted quantile loss (CWQLoss) and its application to probabilistic short and medium-term electric-load forecasting of special interest for smart grids operations. The method allows any point forecast neural netwo...

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Bibliografski detalji
Glavni autori: Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Luis Hernandez-Callejo, Juan Ignacio Arribas, Belen Carro
Format: Članak
Jezik:English
Izdano: MDPI AG 2021-04-01
Serija:Sensors
Teme:
short and medium-term electric-load forecasting
quantile forecasting
deep learning
machine learning
deep learning additive ensemble model
Online pristup:https://www.mdpi.com/1424-8220/21/9/2979

Internet

https://www.mdpi.com/1424-8220/21/9/2979

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