基于人工神经网络算法的用电信息传输冗余量消除仿真  

Simulation of eliminating redundancy in power information transmission based on artificial neural network algorithm

作　　者：余锦河 刘虎 张才俊 YU Jinhe;LIU Hu;ZHANG Caijun(State Grid Customer Service Center,Tianjin 300309,China;State Grid Corporation of China,Beijing 100006,China)

机构地区：[1]国家电网有限公司客户服务中心,天津300309 [2]国家电网有限公司,北京100006

出　　处：《电子设计工程》2023年第23期54-57,62,共5页Electronic Design Engineering

基　　金：国家电网有限公司客户服务中心设计开发项目(71993118000D)。

摘　　要：为缩小用电信息压缩后所占据的存储空间,实现对冗余数据的准确消除,提出基于人工神经网络算法的用电信息传输冗余量消除方法。按照人工神经网络原理,定义冗余用电信息传输格式,根据信息重复率指标的数值水平,实现对冗余用电信息的按需处理。分别从冗余强度、聚合系数两个角度,计算冗余用电信息的压缩量水平,完成基于人工神经网络算法的用电信息传输冗余量消除方法设计。实现结果表明,在人工神经网络算法的作用下,压缩后用电信息所占存储空间缩小至2.66×10^(9)Mb,可避免信息参量的重复出现,从而实现对冗余数据的准确消除处理。In order to reduce the storage space occupied by the compressed power information and realize the accurate elimination of redundant data,a method of eliminating the redundancy of power information transmission based on artificial neural network algorithm is proposed.According to the principle of artificial neural network,the transmission format of redundant power information is defined,and the redundant power information can be processed on demand according to the numerical level of information repetition rate index.From the perspectives of redundancy strength and aggregation coefficient,calculate the compression level of redundant power information,and complete the design of power information transmission redundancy elimination method based on artificial neural network algorithm.The results show that under the action of artificial neural network algorithm,the storage space occupied by compressed power consumption information is reduced to 2.66×10^(9)Mb,which can avoid the repetition of information parameters,so as to realize the accurate elimination of redundant data.

关 键 词：人工神经网络算法 用电信息 冗余消除 信息重复率 聚合系数 压缩量 

分 类 号：TN972.1[电子电信—信号与信息处理]