In this paper, we propose a computational scheme for the problem of wind power forecasting. Such scheme combines a local weighted regression model with fuzzy transform. The latter provides a way to reduce the cardinality of the learning problem, resulting in a more efficient algorithm. Numerical examples show the effectiveness of the proposed approach.
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