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

Energies

Volumn 12, Issue 18, 2019, Pages

  Liu, Fang ^a   Li, Ranran ^a   Dreglea, Aliona ^b  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b IRKUTSK NATIONAL RESEARCH TECHNICAL UNIVERSITY   (Russian Federation)

Author keywords

Linearization; Machine learning; Wind power: wind speed: T S fuzzy model: forecasting

Indexed keywords

BACKPROPAGATION; CLUSTERING ALGORITHMS; FUZZY CLUSTERING; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; LINEARIZATION; MACHINE LEARNING; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; WIND; WIND POWER;

BACK PROPAGATION NEURAL NETWORKS; EMPIRICAL MODE DECOMPOSITION; FUZZY C-MEANS CLUSTERING ALGORITHMS; METEOROLOGICAL MEASUREMENTS; RECURSIVE LEAST SQUARES METHOD; SHORT-TERM WIND POWER FORECASTING; WIND SPEED; WIND SPEED FORECASTING;

WEATHER FORECASTING;

EID: 85072535565     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en12183551     Document Type: Article

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