摘要
负荷预测分为坏数据处理和预测建模 2个步骤 ,目前尚无一种系统化的有效方法对坏数据进行精确的辨识。模糊系统是多因素短期负荷预测建模的一种较好的方法 ,但其结构辨识是一个难点。文中将数据挖掘思想和软计算方法相结合 ,较好地解决了上述问题 ,并对实际数据加以分析 。
Outlier identification and load forecasting modeling are the two steps in short_term load forecasting. There is no acknowledged effective method for outlier identification in electric load data. Fuzzy modeling is an effective method for multi_factor STLF,but fuzzy structure identification is difficult. Data mining and soft computing are combined in this dissertation to solve the problems. Test results using actual data are served for demonstrating the feasibility of the proposed methods.
出处
《江苏电机工程》
2003年第2期1-4,共4页
Jiangsu Electrical Engineering
