摘要
时间序列是按时间顺序排列的一组数据点或观测值,在金融学、气象学和股票市场分析等领域中被广泛应用。时间序列数据出现异常可能意味着出现潜在问题、异常事件或系统故障。为了便于未来在时间序列异常检测方法设计方面开展深入研究,本文首先介绍时间序列异常检测的相关概念;其次,展开分析国内外单变量和多变量时间序列异常检测方法;之后,介绍一些时间序列异常检测通用数据集并比较常见检测方法在这些数据集上的性能;最后,探讨未来时间序列异常检测方法设计的重点研究方向,以期对相关理论和应用研究提供参考。
Time series is a set of data points or observed values arranged in chronological order,which is widely used in the fields of finance,meteorology and stock market analysis.Abnormalities in these data may mean potential problems,abnormal events or system failures.To facilitate further research on the design of anomaly detection methods for time series in the future,the related concepts of time series anomaly detection are introduced firstly.Secondly,the anomaly detection methods for univariate and multivariate time series at home and abroad are analyzed.After that,some general datasets of anomaly detection for time series are introduced and the performance of common methods on these datasets are compared.Finally,the key research directions on the design of anomaly detection method for time series in the future are discussed,which can provide a reference for relevant theoretical and applied research.
作者
谢丽霞
王嘉敏
杨宏宇
胡泽
成翔
张良
XIE Lixia;WANG Jiamin;YANG Hongyu;HU Ze;CHENG Xiang;ZHANG Liang(School of Computer Science and Technology,CACU,Tianjin 300300,China;School of Safety Science and Engineering,CACU,Tianjin 300300,China;Information Security Evaluation Center,CACU,Tianjin 300300,China;School of Information Engineering,Yangzhou University,Yangzhou 225127,Jiangsu,China;School of Information,University of Arizona,Tucson AZ85721,Arizona,USA)
出处
《中国民航大学学报》
CAS
2024年第3期1-12,18,共13页
Journal of Civil Aviation University of China
基金
国家自然科学基金项目(62201576,U1833107)
中央高校基本科研业务费专项(3122022050)
中国民航大学信息安全测评中心开放基金项目(ISECCA-202202)
江苏省基础研究计划自然科学基金青年基金项目(BK20230558)。
