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DB小波与RBP神经网络的短期电力负荷预测
引用本文:张费,宋万清. DB小波与RBP神经网络的短期电力负荷预测[J]. 上海工程技术大学学报, 2009, 23(3): 238-243. DOI: 10.3969/j.issn.1009-444X.2009.03.013
作者姓名:张费  宋万清
作者单位:上海工程技术大学,电子电气工程学院,上海,201620;上海工程技术大学,电子电气工程学院,上海,201620
摘    要:基于DB小波与BP神经网络,提出一种DB小波与RBP神经网络的方法对短期电力负荷预测.运用DB小波能够精确地提取时间序列的细微特性和RBP网络的输出反馈作为输入神经元数据增加了数据信息量的特点,构建了DB与RBP预测模型,经实际数据证明该方法提高了预测的精确性.

关 键 词:短期负荷预测  DB小波  回归BP神经网络

Short-term Load Forecasting for Electric Power System Based on DB Wavelet and RBP Neural Networks
ZHANG Fei,SONG Wan-qing. Short-term Load Forecasting for Electric Power System Based on DB Wavelet and RBP Neural Networks[J]. Journal of Shanghai University of Engineering Science, 2009, 23(3): 238-243. DOI: 10.3969/j.issn.1009-444X.2009.03.013
Authors:ZHANG Fei  SONG Wan-qing
Affiliation:(College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)
Abstract:Based on DB wavelet and the BP neural network,a method of short-term power load forecasting was presented. The forecasting model was provided by using the characteristics of DB wavelet which can decompose time series into any level and RBP network output feedback as input data which can increase information amount. A practical example proves that this method has higher forecasting accuracy in short-term load forecasting.
Keywords:short-term load forecasting  DB wavelet  RBP (Recurrent BP,RBP)neural network
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