多元时间序列相似性搜索研究综述
发布时间:2018-11-06 13:21
【摘要】:多元时间序列相似模式挖掘是数据挖掘领域的研究热点,它主要包括特征表示、相似模式度量和相似性搜索3个方面.目前,大部分研究成果主要集中在特征表示和相似模式度量,相似性搜索则成为制约问题突破的关键环节.为此,主要针对多元时间序列的相似性搜索进行综述,归纳了主要的相似模式度量方法,对比了不同相似模式度量下的序列搜索方法,并分析了不同方法的优缺点,以期为进一步研究多元时间序列相似性搜索提供帮助.
[Abstract]:Multivariate time series similarity pattern mining is a hot topic in the field of data mining. It mainly includes three aspects: feature representation, similarity pattern measurement and similarity search. At present, most of the research results mainly focus on feature representation and similarity pattern measurement, and similarity search becomes the key link to restrict the breakthrough of the problem. Therefore, this paper summarizes the similarity search of multivariate time series, summarizes the main similarity pattern measurement methods, compares the sequence search methods under different similarity pattern metrics, and analyzes the advantages and disadvantages of different methods. In order to provide help for further research on similarity search of multivariate time series.
【作者单位】: 空军工程大学装备管理与安全工程学院;
【基金】:国家自然科学基金项目(61502521,71601183)
【分类号】:TP311.13;O211.61
[Abstract]:Multivariate time series similarity pattern mining is a hot topic in the field of data mining. It mainly includes three aspects: feature representation, similarity pattern measurement and similarity search. At present, most of the research results mainly focus on feature representation and similarity pattern measurement, and similarity search becomes the key link to restrict the breakthrough of the problem. Therefore, this paper summarizes the similarity search of multivariate time series, summarizes the main similarity pattern measurement methods, compares the sequence search methods under different similarity pattern metrics, and analyzes the advantages and disadvantages of different methods. In order to provide help for further research on similarity search of multivariate time series.
【作者单位】: 空军工程大学装备管理与安全工程学院;
【基金】:国家自然科学基金项目(61502521,71601183)
【分类号】:TP311.13;O211.61
【相似文献】
相关期刊论文 前10条
1 杨兴江;周勇;;多元时间序列相似性研究[J];西南民族大学学报(自然科学版);2007年04期
2 李正欣;张凤鸣;张晓丰;杨仕美;;多元时间序列特征降维方法研究[J];小型微型计算机系统;2013年02期
3 李正欣;郭建胜;惠晓滨;宋飞飞;;基于共同主成分的多元时间序列降维方法[J];控制与决策;2013年04期
4 郭小芳;李锋;;多元时间序列聚类算法分析[J];河南师范大学学报(自然科学版);2012年06期
5 吴虎胜;张凤鸣;张超;李正欣;杜继永;;多元时间序列的相似性匹配[J];应用科学学报;2013年06期
6 吴虎胜;张凤鸣;钟斌;;基于二维奇异值分解的多元时间序列相似匹配方法[J];电子与信息学报;2014年04期
7 周勇;林s,
本文编号:2314396
本文链接:https://www.wllwen.com/kejilunwen/yysx/2314396.html