Aiming to estimate for missing data of the electric energy metering and management system, the theory of optimum weighted combination which combined GM(1.1) ,SVM(Support Vector Machines) and ANN are introduced to short-term load forecasting of the system, then the predicted value is get. The forecasting results based on the data from the distribution electricity center in Eastern Slovakia shows that the algorithm possesses evident effectiveness in the field of short-term load forecasting.%通过把灰色系统GM(1,1)、SVM(支持向量机)和人工神经网络预测法进行最优加权组合,引入到电能短期负荷预测系统中,实现企业电能数据缺失的补缺功能.通过对斯洛伐克东部电力中心的历史数据进行试验分析,表明了该算法在电能短期负荷预测方面的有效性.
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