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基于改进尺度的统计建模数据中离群点去除算法及应用
引用本文:张新荣,徐保国.基于改进尺度的统计建模数据中离群点去除算法及应用[J].计算机工程与科学,2011,33(2):168-172.
作者姓名:张新荣  徐保国
作者单位:1. 淮阴工学院电子与电气工程学院,江苏,淮安,223003
2. 江南大学信控学院,江苏,无锡,214122
基金项目:国家863计划资助项目
摘    要:鉴于传统鲁棒离群点去除算法不能准确估计过程采样数据的均值和协方差,导致基于PCA的统计建模监控影响故障诊断效果的局限性,本文提出一种综合CDCm与MVT的异常检测算法,可以克服上述缺陷.通过改进尺度方法对过程原始采样数据实现准确估计并进行中心化和标准化处理,运用采样数据中的最大变量值来计算距离,采用CDCm算法求出样本...

关 键 词:改进尺度  离群点  中心最短距离  椭球多变量整理

The Outlier Detection Algorithm and Its Application in the Statistical Monitoring Model Based on Modified Scaling
ZHANG Xin-rong,XU Bao-guo.The Outlier Detection Algorithm and Its Application in the Statistical Monitoring Model Based on Modified Scaling[J].Computer Engineering & Science,2011,33(2):168-172.
Authors:ZHANG Xin-rong  XU Bao-guo
Abstract:The traditional robust outlier removing algorithm can not obtain the accurate mean and standard deviation of the sample data.Thus it can decrease the ability of processing the fault diagnosis in the statistical monitoring model based on PCA.An outlier detection algorithm which combines CDCm(Closest Distance to Center,Maximum Variable Distance) and MVT(Ellipsoidal Multivariate Trimming) is proposed.It can overcome the above limitations,utilizing a modified scale to obtain the mean and standard deviation of the processing data,and can carry out the centering and standardization of it.Then the normal data of observations and the closest distance to the center are extracted from the modeling database by the CDCm algorithm of maximum variable distance.Using it,the first mahalanobis distance of MVT is obtained.The other normal data is gotten by the iterative calculation of the mahalanobis distance.A method is applied to detecting outliers from a fermentation process and comparing with the traditional robust outlier detection algorithms.The analysis and experimental results show that it can improve the outlier detecting efficiency and accuracy.
Keywords:modified scaling  outlier  closest distance to center  ellipsoidal multivariate trimming
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