High Order Neural Networks for Wind Speed Time Series Prediction

被引:0
|
作者
Alanis, Alma Y. [1 ]
Ricalde, Luis J. [2 ]
Sanchez, Edgar N. [3 ]
机构
[1] Univ Guadalajara, CUCEI, Apartado Postal 51-71,Col Las Aguilas, Zapopan 45080, Jalisco, Mexico
[2] UADY, Fac Engn, Yucatan, Mexico
[3] CINVESTAV, Jalisco, Mexico
关键词
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
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页码:2193 / +
页数:2
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