云南民族大学学报（自然科学版）2017，Vol.26Issue(6)：497-501,5.DOI:10.3969/j.issn.1672-8513.2017.06.013
基于BP神经网络的关口电能计量 装置测量误差预测及校正
Error prediction and correction of gate energy measurement based on BP neural network
摘要
Abstract
Improving the accuracy of gate energy measurement is very important and worthwhile. In this paper, the historical data of the gate energy measurement are analyzed, and the BP ( Back Propagation) neural network algo-rithm is used to predict the error. The optimal model of the metrological data is selected to correct the abnormal val-ue, thus reducing the impact of the gate energy measurement error, and improving the accuracy of energy measure-ment. Experiments show that this error prediction and correction model can accurately predict the error of the gate energy measurement and correct the abnormal value.关键词
关口电能计量/BP神经网络/误差预测/误差校正Key words
gate energy measurement/BP neural network/error prediction/error correction分类
信息技术与安全科学引用本文复制引用
王昕,曹敏,江雄,赵艳峰,李翔,赵旭,蒋婷婷,原野..基于BP神经网络的关口电能计量 装置测量误差预测及校正[J].云南民族大学学报（自然科学版）,2017,26(6):497-501,5.基金项目
国家自然科学基金(61263043). （61263043）
