Application of Core Vector Regression in Condition-Based Maintenance for Electric Power Equipments
In this paper, we propose a forecasting model of electric power equipment statement assembled by core vector machines and particle swarm algorithm to improve the accuracy of electric equipment maintenance. The electric power equipment condition forecasting model improves parameter selection problems of nuclear vector regression by particle swarm algorithm, optimizes parameters of kernel function and reduces the artificial factors in the forecasting process; accordingly reduces the blindness in the process of training and improves the accuracy of the prediction, while core vector regression have the advantages of high precision, suitable for power equipment maintenance process.
electric power equipment condition-based maintenance particle swarm algorithm core vector regression
Junhua Qu Wenjuan Wang Chao Wei
School of Control and Computer Engineering North China Electric Power University Beijing, China
国际会议
秦皇岛
英文
429-432
2010-11-05（万方平台首次上网日期，不代表论文的发表时间）