Dynamic Extraction Model of Power Transaction Data Based on Weighted FCM Clustering Algorithm
Massive and redundant power transaction data greatly hinder the decision-making of power transaction.Therefore,a dynamic extraction model of power transaction data based on weighted FCM clustering algorithm is studied.This paper gathers the preprocessed power transaction data,compress the data volume,sort and process the power transaction data based on the full arrangement theory,extract the power transaction data characteristics(volatility,trend and variability characteristics),take them as the weighting basis of FCM clustering algorithm,obtain the corresponding weighting matrix,and apply the weighted FCM clustering algorithm to cluster and extract the required power transaction data.The dynamic extraction of power transaction data is realized.The experimental data show that the clustering parameter DBI value of power transaction data ob-tained by the model is small,the DVI value is large,the dynamic extraction time of power transaction data is short,and the ap-plication performance is better.
万方数据
维普
