A Hybrid Wind Speed Forecasting System Based on a ‘Decomposition and Ensemble’ Strategy and Fuzzy Time Series
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Title
A Hybrid Wind Speed Forecasting System Based on a ‘Decomposition and Ensemble’ Strategy and Fuzzy Time Series
Authors
Keywords
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Journal
Energies
Volume 10, Issue 9, Pages 1422
Publisher
MDPI AG
Online
2017-09-19
DOI
10.3390/en10091422
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- A review of combined approaches for prediction of short-term wind speed and power
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- (2013) ChienHsing Wu et al. INFORMATION SCIENCES
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- A Fuzzy Group Forecasting Model Based on Least Squares Support Vector Machine (LS-SVM) for Short-Term Wind Power
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- (2011) C. Hervás-Martínez et al. NEURAL COMPUTING & APPLICATIONS
- Optimization methods applied to renewable and sustainable energy: A review
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