Because the existing bit error rate of mining methods is greater than 0.2 BER and the mining accuracy is low,we study the overload data mining of digital power network under gray correlation analysis.The gray correlation analysis method is used to process the data and dig out the degree of correlation between various factors.The data were subjected to the clustering analysis to obtain the different sample types.The training set is used to build a decision tree model and calculate the difference degree of the generated data.Using the mining discrimination function of digital power network overload data for data mining.The experimental results show that the data sequence in different time points;the mining error rate of overload data in 10 groups is 0～0.2 BER,which can mine overload data accurately and achieve good mining effect.
维普
万方数据
