JET: Fast Estimation of Hierarchical Time Series Clustering-Reference-Cited by-同舟云学术

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JET: Fast Estimation of Hierarchical Time Series Clustering

Published:2024-07-11 Issue: Volume:10 Page:37
ISSN:
Container-title:ITISE 2024
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Author:

Wenig Phillip¹^ORCID,Höfgen Mathias²,Papenbrock Thorsten³^ORCID

Affiliation:

1. Hasso Plattner Institute, University of Potsdam, 14469 Potsdam, Germany

2. Rolls-Royce Deutschland Ltd. & Co. KG, 15827 Blankenfelde-Mahlow, Germany

3. Department of Mathematics and Computer Science, Philipps University of Marburg, 35037 Marburg, Germany

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/68/1/37/pdf

Reference36 articles.

1. A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records;Ansari;IEEE Rev. Biomed. Eng.,2017

2. Woike, M., Abdul-Aziz, A., and Clem, M. (2014, January 10–11). Structural health monitoring on turbine engines using microwave blade tip clearance sensors. Proceedings of the Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2014, San Diego, CA, USA.

3. Cheng, H., Tan, P.N., Potter, C., and Klooster, S. (May, January 30). Detection and Characterization of Anomalies in Multivariate Time Series. Proceedings of the SIAM International Conference on Data Mining (SDM), Sparks, NV, USA.

4. Braei, M., and Wagner, S. (2020). Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art. arXiv.

5. Blázquez-García, A., Conde, A., Mori, U., and Lozano, J.A. (2020). A Review on Outlier/Anomaly Detection in Time Series Data. arXiv.

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