High Order Neural Networks for wind speed time series prediction
Published 1 June 2009
Alma Y. Alanís, Luis J. Ricalde, Edgar N. Sánchez
Citations21
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TL;DR
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.
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.
Keywords
Computer ScienceEngineering
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