Application of dynamic granularity combined with center point algorithm in power equipment defect control
Aiming at the problem of power equipment defect control,the study proposes a power equipment defect control model based on the improved k-center point clustering algorithm and dynamic granularity.The study first uses the improved k-center point clustering algorithm to cluster the equipment defect data;then combines the dynamic granularity with the improved algorithm for constructing the defect control model.The results show that the data clustering correct rate of the defect control model is 93.07％,and the clustering efficiency can reach 90.07％,meanwhile,the data recognition accuracy,recall rate and Fl value are 93.27％,93.52％and 0.951 respectively,which are better than the comparison method.This indicates that the power equipment defect control model constructed in the study can significantly improve the reliability and stability of the equipment.
dynamic granularityk-center point clustering algorithmpower equipmentdefect control
万方数据
维普
