%0 Journal Article
%T A Novel Discords Detector for Periodic Time Series Based on Weighted Spherical Single Means with Phase Shift<br>基于移相加权球面单簇聚类的周期时间序列异常检测
%A WANG Jun
%A CHUNG Fu-Lai
%A WANG Shi-Tong
%A DENG Zhao-Hong
%A <br>王骏
%A 钟富礼
%A 王士同
%A 邓赵红
%J 自动化学报
%D 2011
%I 
%X The traditional one-class classifiers are not suitable for detecting discords in periodic time series. A novel one-class classifier PS-WS1M-OCC is proposed in this paper. In our method, the phase problem in time series is solved by introducing phase shift into the clustering procedure. Meanwhile, a novel criterion for adaptively choosing threshold is proposed. In this way, the proposed classifier is insensitive to noise in the training set. Experimental results show that our PS-WSKM-OCC is more robust than the existing one-class classifiers when it is applied to the problem of discord detection in the periodic time series.
%K Weighted spherical single means with phase shift
%K discord detection
%K one-class classifier
%K learning from noise data<br>移相加权球面单簇聚类
%K 时间序列异常检测
%K 单分类器
%K 从包含噪声的数据中学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=4C887890006522007DDEB3E7CC6ABB3A&yid=9377ED8094509821&vid=42425781F0B1C26E&iid=5D311CA918CA9A03&sid=CEA1F7DC6B978724&eid=E1034A3BCFB43055&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=13