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Unsupervised Multivariate Time Series Anomaly Detection via Transformer-Based Models and Time Series Encoding

机译：无监督的多变量时间序列异常检测通过基于变压器的模型和时间序列编码

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作者
Duan, Tinglin.;
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作者单位

University of Toronto (Canada).;

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授予单位 University of Toronto (Canada).;
学科
学位 M.A.S.
年度 2021
页码 93 p.
总页数 93
原文格式 PDF
正文语种 eng
中图分类
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2. Multivariate time series anomaly detection: A framework of Hidden Markov Models [J] . Li Jinbo, Pedrycz Witold, Jamal Iqbal Applied Soft Computing . 2017,第期

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3. Multivariate Time-Series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing: Application to Early Acute Hypotensive Episode Detection [J] . Jwala Dhamala, Emmanuel Azuh, Abdullah Al-Dujaili, IEEE Sensors Letters . 2019,第1期

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4. VGG Based Unsupervised Anomaly Detection in Multivariate Time Series [C] . Grzegorz Jablonski Polish Control Conference . 2020

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5. Advanced Data Analytics Methodologies for Anomaly Detection in Multivariate Time Series Vehicle Operating Data [D] . Alizadeh, Morteza. 2021

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6. Multivariate-Time-Series-Driven Real-time Anomaly Detection Based on Bayesian Network [O] . Nan Ding, Huanbo Gao, Hongyu Bu, 2018

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7. A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data [O] . Chuxu Zhang, Dongjin Song, Yuncong Chen, 2019

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8. Information Fusion Based Decision Support via Hidden Markov Models and Time Series Anomaly Detection [R] . Barker, J., Green, R., Thomas, P., 2009

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Unsupervised Multivariate Time Series Anomaly Detection via Transformer-Based Models and Time Series Encoding

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