Zhenhua Guo1,2, Lixin Zhang1,*, Xue Hu1, Huanmei Chen2
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941
Abstract Wind speed prediction is an important part of the wind farm management and
wind power grid connection. Having accurate prediction of short-term wind
speed is the basis for predicting wind power. This paper proposes a short-term
wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four
wavelet neural network models using the Morlet function as the wavelet basis
function were developed to forecast short-term wind speed in January, April,
July, and October. Predicted wind speed was compared across the four models
using the mean square error and regression.… More >
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