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Short-term wind power forecasting based on T-S fuzzy model

... the main affecting factors are selected by means of the correlation analysis for wind power prediction. Then, the antecedent and the consequent parameters of the forecasting model are identified by the fuzzy c-means (FCM) clustering algorithm and the recursive least squares method (RLS). Finally, the T-S fuzzy model for wind power short-term forecasting is obtained. The stationary wind periods are considered as the cases to validate the proposed forecasting method. The forecasting results are compared ...

Теги: fuzzy c-means (fcm) , recursive least squares method (rls) , t-s fuzzy model , wind power forecasting , clustering algorithms , forecasting , fuzzy systems , least squares approximations , signal processing , support vector machines , wind , wind effects , wind power
Раздел: ИСЭМ СО РАН


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