摘要
由于传统IT终端设备运行异常检测方法的检出率较低,导致设备运维难度加大,所以提出基于数据挖掘的IT终端设备运行异常检测方法。利用无线传感器获取IT终端设备运行数据,采用多阶拉格朗日差值法清洗采集到的数据,并对数据做降维处理。利用数据挖掘技术对设备运行数据进行关联分析,根据当前设备运行模式与规则库的相似度,判断IT终端设备是否处于异常运行状态,实现IT终端设备运行异常检测。经实验证明,所设计方法的平均检出率为98.76%,具有较高的检测精度,在IT终端设备运行异常检测方面具有良好的应用前景。
Due to the low detection rate of the traditional IT terminal equipment operation abnormality detection method,which makes the equipment operation and maintenance more difficult,a data mining based IT terminal equipment operation abnormality detection method is proposed.The wireless sensor is used to obtain the operation data of IT terminal equipment,and the multi-level Lagrange difference method is used to clean the collected data,and the data is processed in dimension reduction.The data mining technology is used to perform association analysis on the equipment operation data.According to the similarity between the current equipment operation mode and the rule base,it is judged whether the IT terminal equipment is in an abnormal operation state,and the IT terminal equipment operation abnormality detection is realized.The experimental results show that the average detection rate of the designed method is 98.76%,which has a high detection accuracy and has a good application prospect in the abnormal operation detection of IT terminal equipment.
作者
毛雯新
MAO Wenxin(Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen Guangdong 518000)
出处
《软件》
2023年第4期161-163,共3页
Software
关键词
数据挖掘
IT终端设备
异常检测
检出率
多阶拉格朗日差值法
data mining
IT terminal equipment
abnormality detection
detection rate
multi order Lagrange difference method
