安徽农业科学2009，Vol.37Issue(30)：14892-14893,14922,3.
基于改进神经网络的农村电力系统短期负荷预测
Rural Short-term Load Forecasting of Power System Based on Improved Neural Network
摘要
Abstract
In order to improve capacity of rural short-term load forecasting model of power system and make short term load forecasting more accurate and fast, Levenberg-Marquardt algorithm based on optimization theory was adopted to improve the traditional BP algorithm, and the power system load forecasting model was constructed. TheResults showed that the neural network forecasting model based on L-M algorithm has higher prediction accuracy and a high value in the rural power system short-term load forecasting.关键词
BP神经网络/L-M算法/电力系统短期负荷Key words
BP neural network/ L-M algorithm/ Power system short-term load分类
信息技术与安全科学引用本文复制引用
张师玲,李正明,周新云,孙俊,张兵..基于改进神经网络的农村电力系统短期负荷预测[J].安徽农业科学,2009,37(30):14892-14893,14922,3.基金项目
江苏省教育厅资助项目(JHZD06-42) （JHZD06-42）
江苏省常州市青年科技人才培养计划(CQ2008009). （CQ2008009）
