| A cosine similarity-based negative selection algorithm for time series novelty detection | |
| Dong, YG ; Sun, ZY ; Ha, HB | |
| 2010-05-10 ; 2010-05-10 | |
| 关键词 | NETWORKS Engineering, Mechanical |
| 中文摘要 | Detecting the new or anomalous signal sequences in the observed time series data is a problem of great practical interest for many applications. The bio-inspired negative selection algorithm, whose main idea is to discriminate the non-self pattern from self pattern, has drawn much attention because only normal information is needed for training. Most of the proposed algorithms are based on binary-valued string matching. A real-valued negative selection algorithm for novelty detection in vibration signal is implemented in this paper. The vector set for calculation is constructed by sampling the discrete time series from a moving time window. The matching affinity between two vectors is measured by cosine similarity. The calculated results show that the cosine similarity-based algorithm is more practical for potential applications in online signal monitoring. (c) 2005 Elsevier Ltd. All rights reserved. |
| 语种 | 英语 ; 英语 |
| 出版者 | ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD ; LONDON ; 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND |
| 内容类型 | 期刊论文 |
| 源URL | [http://hdl.handle.net/123456789/24357]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | Dong, YG,Sun, ZY,Ha, HB. A cosine similarity-based negative selection algorithm for time series novelty detection[J],2010, 2010. |
| APA | Dong, YG,Sun, ZY,&Ha, HB.(2010).A cosine similarity-based negative selection algorithm for time series novelty detection.. |
| MLA | Dong, YG,et al."A cosine similarity-based negative selection algorithm for time series novelty detection".(2010). |
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