计算机应用与软件Issue(2)：171-173,3.DOI:10.3969/j.issn.1000-386x.2014.02.046
基于气象因子Fuzzy模糊处理的短期电力负荷预测
SHORT-TERM LOAD FORECASTING WITH FUZZY PROCESSING BASED ON METEOROLOGICAL FACTORS
摘要
Abstract
Short-term power load forecasting is impacted by various meteorological factors,which affected its forecasting accuracy.We use fuzzy logic to deal with three influencing factors:the temperature,the humidity and the wind speed,and convert them into specific data which can be inputted and recognised by BP neural network.After being trained,the fuzzy set neural network gets appropriate weight.Using the trained neural network to test daily power load data,the forecasted average errors is about ±1 .69%.关键词
短期负荷预测/神经网络/模糊逻辑/BP算法Key words
Short-term load forecasting/Neural network/Fuzzy logic/BP algorithm分类
信息技术与安全科学引用本文复制引用
黄亮亮,王勇,杨恒,陈帅..基于气象因子Fuzzy模糊处理的短期电力负荷预测[J].计算机应用与软件,2014,(2):171-173,3.基金项目
信息安全国家重点实验室（中国科学院软件研究所）开放式基金项目（04-02-1）；上海教委创新基金项目（11 YZ192）；上海市“科技创新行动计划”重点项目（11511504400）。 （）
