信阳师范学院学报（自然科学版）2012，Vol.25Issue(4)：555-559,5.DOI:10.3969/j.issn.1003-0972.2012.04.033
多元时间序列模式异常研究
Outlier Pattern Research of Multivariate Time Series
摘要
Abstract
In order to improve the efficiency of outlier model detection algorithm of multivariate time series ( MTS) , based on the k-nearest neighbor local outlier detection algorithm, the principal component analysis of the multivariate time series method for dimensionality reduction method was used to detect anomalies of multivariate time series model. The experimental results show that the proposed algorithm detects MTS outlier pattern series more accurately and more efficiently关键词
多元时间序列/主元分析/κ-近邻/模式异常检测Key words
multivariate time series/ principal component analysis/ k-nearest neighbor/ pattern outlier detection分类
信息技术与安全科学引用本文复制引用
郭小芳,李锋,叶华..多元时间序列模式异常研究[J].信阳师范学院学报（自然科学版）,2012,25(4):555-559,5.基金项目
江苏省高校自然科学研究项目(10JKB520006) （10JKB520006）
