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最优加权组合法在电能短期负荷预测中的应用
引用本文:王典,蔡琼.最优加权组合法在电能短期负荷预测中的应用[J].计算机与现代化,2012(7):188-191.
作者姓名:王典  蔡琼
作者单位:武汉工程大学计算机科学与工程学院,湖北武汉430073
摘    要: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。

关 键 词:短期负荷预测  灰色系统GM(1  1)  支持向量机  人工神经网络

Application of Optimum Weighted Combination Method in Electric Power Short-term Load Forecasting
WANG Dian,CAI Qiong.Application of Optimum Weighted Combination Method in Electric Power Short-term Load Forecasting[J].Computer and Modernization,2012(7):188-191.
Authors:WANG Dian  CAI Qiong
Affiliation:(School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430075, China)
Abstract: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.
Keywords:short-term load forecasting  GM(1  1)  SVM  ANN
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