摘要
针对当前铁路电力自动化系统可靠性评估过程存在的问题,以获得更加理想的评估效果,提出了人工智能技术的铁路电力自动化系统可靠性评估模型。首先分析铁路电力自动化系统可靠性评估研究进展,指出各种评估模型存在的局限性;然后提取铁路电力自动化系统可靠性特征,将特征作为最小二乘支持向量的输入向量,采用粒子群算法搜索最小二乘支持向量最优参数,建立铁路电力自动化系统可靠性评估模型;最后与其他铁路电力自动化系统可靠性评估模型进行了仿真对比实验。结果表明,人工智能技术的铁路电力自动化系统可靠性评估准确度高,平均耗时短,评估整体性能明显优于其他模型,为解决铁路电力自动化系统可靠性评估提供了一种新的研究工具。
In view of the problems existing in the reliability evaluation process of railway electric power automation system at present,in order to obtain more ideal reliability evaluation effect of railway electric power automation system,the reliability evaluation model of railway electric power automation system based on artificial intelligence technology is proposed.Firstly,the research progress of reliability evaluation of railway electric power automation system is analyzed,and the limitations of various evaluation models are pointed out.Secondly,we extract the reliability characteristics of railway power automation system,as the input vector of least square support vector,use particle swarm optimization algorithm to search the optimal parameters of least square support vector,establish the reliability evaluation model of railway power automation system,and carry out simulation and comparison experiments with other reliability evaluation models of railway power automation system.The results show that the reliability evaluation of the railway power automation system based on artificial intelligence technology has high accuracy,short average time and obvious overall performance,which provides a new research tool for solving the reliability evaluation of the railway power automation system.
作者
周明
ZHOU Ming(Beijing China Railway Construction Electrification Design and Research Institute Co.,Ltd,.Beijing 100043,China)
出处
《电气应用》
2020年第6期35-39,共5页
Electrotechnical Application
关键词
人工智能技术
铁路电力
自动化系统
粒子群算法
评估效果
artificial intelligence technology
railway power
automation system
particle swarm optimization algorithm
evaluation effect
