基于神经网络的量测数据检测及修正系统研究应用

Research and Application of Measurement Data Detection and Correction System Based on Neural Network

为解决电力系统数据量测过程中的不确定性因素和非线性计算等问题,首先构建了基于缩减聚类算法的神经网络最优模型,然后通过反向传播算法建立量测数据模型,最后针对可信量测数据与可疑量测数据给出了相应的解决办法,整体建立了一套智能量测数据检测与修正系统。

In order to solve the problems of uncertain factors and nonlinear calculation in the process of power system data measurement, this paper first constructs the neural network optimal model based on reduced clustering algorithm, then establishes the measurement data model through back propagation algorithm, and finally gives the corresponding solutions for trusted measurement data and suspicious measurement data, and establishes an intelligent measurement data detection and correction system.