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Description: Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.
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