摘要
针对电力调度自动化设备健康评估过程中存在的评估方式简单、评估方式可解释性弱以及评估效果不精确的问题,本文提出了一种基于模糊神经网络的电力自动化设备健康评估模型.用模糊理论进行分析,用模糊集合描述评价指标,用数据指标的隶属度描述设备运行情况,结合神经网络的自适应功能,针对个体设备提供更加准确的、更具个性化的健康评估.
A health assessment model for power automation equipment based on fuzzy neural network is proposed to solve the problem that the evaluation method is simple,the evaluation method is weak,and the evaluation effect is inaccurate.Using fuzzy theory to analyze,use fuzzy sets to describe evaluation indicators,and use the degree of membership to describe equipment status,combining the adaptive function of neural network to provide more accurate and personalized health evaluation for individual devices.
作者
李鹏
李丹
李喜旺
高宇
LI Peng;LI Dan;LI Xi-Wang;GAO Yu(University of Chinese Academy of Sciences,Beijing 100049,China;Shenyang Institute of Computing Technology,Chinese Academy of Sciences,Shenyang 110168,China;State Grid Corporation Northeast Division,Shenyang 110180,China;California State University,Fullerton,CA 92834,USA)
出处
《计算机系统应用》
2019年第2期207-212,共6页
Computer Systems & Applications
基金
国家科技重大专项(2017ZX01030-201)~~
关键词
模糊神经网络
自动化设备
健康评估
fuzzy network
automation equipment
evaluate device status
