High order neural networks for wind speed time series prediction

Authors:
Alma Y. Alanis;Luis J. Ricalde;Edgar N. Sanchez
Affiliations:
CUCEl, Universidad de Guadalajara, Zapopan, Jalisco, Mexico;Faculty of Engineering, UADY, Yucatan, Mexico;ClNVESTAV, Unidad Guadalajara, Guadalajara, Jalisco, Mexico
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 4
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Abstract

In this paper, we propose a High Order Neural Network (HONN) trained with an extended Kalman filter based algorithm to predict wind speed. Due to the chaotic behavior of the wind time series, it is not possible satisfactorily to apply the traditional forecasting techniques for time series; however, the results presented in this paper confirm that HONNs can very well capture the complexity underlying wind forecasting; this model produces accurate one-step ahead predictions.