基于数据挖掘的轨道交通车辆信号系统分析平台

IF 3.3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Informatica Pub Date : 2023-05-30 DOI:10.31449/inf.v47i3.3942
Chunying Li, Zhonghua Mu
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引用次数: 0

摘要

针对轨道交通车载信号设备对交互信息日益增长的需求,设计了一种基于数据挖掘的轨道交通车载监控维护系统,对运行数据采集设置关联规则,并提出了一种关联规则算法,对列车运行信息进行更可靠的理解和运行质量评价。从大量的日志中,快速发现关键问题,应用于列车测试和维修领域。仿真实验结果表明,经过对仿真数据和曲线的分析,系统提取结果在人工计算结果中存在一定的误差,误差值在0.5 ~ 0.6之间,但总体上满足实际工作需要,并对无效数据进行了优化,减小了误差。验证了系统运行可靠,可维护性好。
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Analysis Platform of Rail Transit Vehicle Signal System Based on Data Mining
According to the increasing demand of interactive information of rail transit on-board signal equipment, the author designed a rail transit on-board monitoring and maintenance system based on data mining to set association rules for operation data acquisition and propose a correlation rules algorithm to obtain more reliable understanding and operation quality evaluation of train operation information.From a lot of logs, quickly find key issues, applied in the train test and repair field.The simulation experiment results show that after analyzing the simulation data and the curve, the system extraction results have certain error in the manual calculation results, and the error value is between 0.5 and 0.6, but the overall meets the actual work needs, and optimize the invalid data to reduce the error.The reliable operation and maintainability of the system are verified.
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来源期刊
Informatica
Informatica 工程技术-计算机:信息系统
CiteScore
5.90
自引率
6.90%
发文量
19
审稿时长
12 months
期刊介绍: The quarterly journal Informatica provides an international forum for high-quality original research and publishes papers on mathematical simulation and optimization, recognition and control, programming theory and systems, automation systems and elements. Informatica provides a multidisciplinary forum for scientists and engineers involved in research and design including experts who implement and manage information systems applications.
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