According to nonlinear feature of various factors related to wind speed, the method of least squares support vector machine (LS-SVM) for short-term wind speed prediction was put forward in this paper. The influence of parameters selection of LS-SVM on prediction accuracy was analyzed. The genetic algorithm was adopted to realize parameters optimization of LS-SVM and establish short-term wind speed prediction model of LS-SVM based on Genetic Algorithm. It was verified that the method proposed in this paper can quickly and effectively carry on short-term wind speed prediction by simulation example. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Han, X., Zhang, X., & Gao, B. (2012). Short-term wind speed prediction model of LS-SVM based on genetic algorithm. In Advances in Intelligent and Soft Computing (Vol. 116 AISC, pp. 221–229). https://doi.org/10.1007/978-3-642-11276-8_28
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