广东电力2016，Vol.29Issue(9)：89-93,5.DOI:10.3969/j.issn.1007-290X.2016.09.018
基于GRNN的二次设备在线监测信息预测
Online Monitoring Information Forecast for Secondary Equipment Based on GRNN
摘要
Abstract
In allusion to continuous information in online monitoring information of grid secondary equipment such as power source voltage,device temperature,CPU usage rate and so on,generalized regression neural network (GRNN)is used for forecasting changes of the information. By comparing predicted value and actual value,relative error curve is obtained. It is verified higher veracity of GRNN in forecast by comparing with back propagation (BP)neural network and radial basis function (RBF)neural network. Meanwhile,this paper discusses to take relevance of online monitoring information of sec-ondary equipment into consideration as well as relate temperature to CPU usage rate for prediction. According to compari-son results,it is proved that it is useful to improve veracity of state prediction by taking relevance of information into consid-eration.关键词
二次设备/在线监测信息/广义回归神经网络/关联性/径向基神经网络/预测Key words
secondary equipment/online monitoring information/generalized regression neural network (GRNN)/rele-vance/radial basis function(RBF)neural network/forecast分类
信息技术与安全科学引用本文复制引用
李金,苗帅,陶文伟,张喜铭,丁坚勇,朱海龙..基于GRNN的二次设备在线监测信息预测[J].广东电力,2016,29(9):89-93,5.基金项目
中国南方电网有限责任公司科技项目(K-ZD2014-011) （K-ZD2014-011）
