Short-Term Forecasting for Energy Consumption through Stacking Heterogeneous Ensemble Learning Model
In the real-life, time-series data comprise a complicated pattern, hence it may be challenging to increase prediction accuracy rates by using machine learning and conventional statistical methods as single learners. This research outlines and investigates the Stacking Multi-Learning Ensemble (SMLE)...
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| Autori principali: | , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2018-06-01
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| Serie: | Energies |
| Soggetti: | |
| Accesso online: | http://www.mdpi.com/1996-1073/11/6/1605 |
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