Wind power forecasting using the k-nearest neighbors algorithm

The paper deals with a modeling procedure which aims to predict the power output of wind farm electricity generators. The following modeling steps are proposed: factor selection, raw data pretreatment, model evaluation and optimization. Both heuristic and formal methods are combined to construct the model. The basic modeling approach here is the k-nearest neighbors method.

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Year of publication:	2014
Authors:	Mangalova, E. ; Agafonov, E.
Published in:	International Journal of Forecasting. - Elsevier, ISSN 0169-2070. - Vol. 30.2014, 2, p. 402-406
Publisher:	Elsevier
Subject:	Cross-validation \| Data mining \| Energy forecasting* \| Forecasting competitions* \| Feature selection \| Nonparametric models \| Regression tree

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010753455