摘要
针对电力行业人子系统可靠性分析难以量化的现状,采用支持向量机进行分析评价,首先分析了电力行业人子系统可靠性及其影响因素;在此基础上,利用k均值聚类,将人子系统可靠性等级划分为4类;然后利用支持向量机,构建了可靠性等级与影响因素之间的显性映射;最后利用判别函数,研究可靠性等级在各个影响因素方面的变化关系。实例分析表明该方法具有较好的推广能力。
Aiming at the current situation that the reliability analysis of the human subsystem in the power industry is difficult to quantify,the support vector machine is used for analysis and evaluation.Firstly,the reliability of the human subsystem in the power industry and its influencing factors are analyzed.On this basis,the k-means clustering is used to transform the human being.The system reliability grade is divided into four categories.Then the support vector machine is used to construct the explicit mapping between the reliability level and the influencing factors.Finally,the discriminant function is used to study the relationship between the reliability level and the influencing factors.The case study shows that the method has a good generalization ability and is of practical significance.
作者
王鹏
董建房
缪列昌
WANG Peng;DONG Jianfang;MIAO Liechang(Basic Department,The People’s Liberation Army Army Artillery Air Defense Academy,Hefei 230031,China;Graduate Brigade,The People’s Liberation Army Army Artillery Air Defense Academy,Hefei 230031,China)
出处
《重庆理工大学学报(自然科学)》
CAS
北大核心
2020年第10期255-258,共4页
Journal of Chongqing University of Technology:Natural Science
基金
安徽省自然科学基金资助项目(1408085MA06)。
关键词
K均值聚类
支持向量机
人子系统
可靠性
k-means clustering
support vector machine
human subsystem
reliability