中文说明：
基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。
English Description：
Based on the theory of least squares support vector machine (LSSVM), combined with the measured wind speed data of a wind farm, the wind speed prediction model of LSSVM is established. The wind speed of the wind farm is predicted one hour in advance, and the average absolute percentage error is only 8.55, so the prediction effect is ideal. At the same time, the wind speed prediction model in this paper is compared with the wind speed prediction model based on neural network theory and support vector machine (SVM) theory. Simulation results show that the proposed model is superior to other models in prediction accuracy and operation speed.