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Wind speed and power ultra short-term robust forecasting based on Takagi–Sugeno fuzzy model

Liu F., Li R., Dreglea A. Wind speed and power ultra short-term robust forecasting based on Takagi–Sugeno fuzzy model // Energies. Vol.12. No.18. ID: 3551. 2019. DOI: 10.3390/en12183551 Accurate wind power and wind speed forecasting remains a critical challenge in wind power systems management. This paper proposes an ultra short-time forecasting method based on the Takagi–Sugeno (T–S) fuzzy model for wind power and wind speed. The model does not rely on a large amount of historical data and can...

Теги: linearization , machine learning , wind power: wind speed: t–s fuzzy model: forecasting , backpropagation , clustering algorithms , fuzzy clustering , learning systems , least squares approximations , neural networks , support vector machines , wind , wind power , b
Раздел: ИСЭМ СО РАН


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