Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emis...

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Bibliographic Details
Main Authors: Federico Divina, Aude Gilson, Francisco Goméz-Vela, Miguel García Torres, José F. Torres
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Energies
Subjects:
ensamble learning
time series forecasting
energy consumption forecasting
evolutionary computation
neural networks
regression
Online Access:http://www.mdpi.com/1996-1073/11/4/949

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http://www.mdpi.com/1996-1073/11/4/949

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