基于蜜蜂进化遗传算法优化SVM的超短期风电功率预测

Ultra short term wind power prediction based on Bee Evolutionary Genetic Algorithm to optimize SVM

提出了基于蜜蜂进化型遗传算法优化支持向量机(SVM)的超短期风电功率预测方法。针对遗传算法在优化支持向量机参数存在的早熟问题,提出了将蜜蜂进化型遗传算法应用于优化支持向量机参数,提高了搜索效率。通过某风电场预测数据进行对比实验,验证了该方法可以有效提高预测准确率和精度。

An ultra short term wind power prediction method based on bee evolutionary genetic algorithm （SVM） is proposed. Aiming at the premature problem of genetic algorithm in optimizing the parameters of support vector machines, it is proposed that the bee evolutionary genetic algorithm is applied to optimize the parameters of support vector machines, and the search efficiency is improved. Through the comparison experiment of a wind farm prediction data, it is proved that this method can effectively improve the prediction accuracy and accuracy.