摘要
针对当前现代电子设备运行状态辨识错误率大、耗时过程长等局限性,为了改善现代电子设备运行状态辨识正确率,设计基于数据挖掘技术的现代电子设备运行状态辨识方法。首先采集电子设备运行状态数据,采用小波变换对数据进行预处理,并提取电子设备运行状态特征,然后采用数据挖掘技术分析电子设备运行状态变化规律,建立辨识模型,最后与其它方法进行电子设备运行状态辨识对比实验。实验结果表明,所提方法的电子设备运行状态辨识正确率高,将辨识误差控制在10%以内,不仅完全可以满足现代电子设备的实际应用要求,而且辨识整体效果要优于对比方法,具有十分明显的优越性。
In order to improve the accuracy of modern electronic equipment operation state identification,a modern electronic equipment operation state identification method based on data mining technology is designed.Firstly,the operation state data of electronic equipment are collected,the data are preprocessed by wavelet transform,and the operation state characteristics of electronic equipment are extracted.Then,the change law of electronic equipment operation state is analyzed by data mining technology,and the identification model is established.Finally,the comparison experiment of electronic equipment operation state identification with other methods is carried out.The results show that the method in this paper has a high accuracy of electronic equipment operation state identification,and the identification error is excavated within 10%,which can meet the practical application requirements of modern electronic equipment,and the overall effect of identification is better than the comparison method,which has very obvious advantages.
作者
刘妍萍
LIU Yan-ping(Xi'an University of Engineering,Xi'an 710048 China)
出处
《自动化技术与应用》
2024年第3期148-151,共4页
Techniques of Automation and Applications
基金
陕西省科技厅重点研发计划项目(2021GY-261)。
关键词
现代电子设备
状态辨识
数据挖掘
测试实验
最优参数
modern electronic equipment
state identification
data mining
test experiment
optimal parameters
