Combining Dynamic Programming and GPU to accelerate k-Distance Discord Detection in Time Series Data-Reference-Cited by-同舟云学术

Combining Dynamic Programming and GPU to accelerate k-Distance Discord Detection in Time Series Data

Published:2023-10-27 Issue: Volume:11486 Page:106-113
ISSN:
Container-title:The 6th International Conference on Machine Learning and Machine Intelligence
language:
Short-container-title:

Author:

Nhan Nguyen Trong¹^ORCID,Anh Duong Tuan²^ORCID,Dvorsky Jiri³^ORCID

Affiliation:

1. Center for Applied Information Technology, Ton Duc Thang University, Vietnam and Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB Technical University, Czech Republic

2. Department of IT, Ho Chi Minh City University of Foreign Languages and Information Technology, Vietnam

3. Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB Technical University, Czech Republic

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3635638.3635654

Reference22 articles.

1. HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence

2. Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

3. S. Nicoli, J.A. Jargini, L.G. Magrini, C. D. M. Miranda, “Detection of nonconformities in monitoring system's measurements”,IEEE PES Conference on Innovative Smart Grid Technologies - Latin America (ISGT LA), Sao Paulo, 15–17 April, 2013.

4. M. Munir, S. Erkel, A. Dengel, S. Ahmed, “Pattern based contextual anomaly detection in HVAC systems”, Proceedings of IEEE International Conference on Data Mining Workshops (ICDMW), pp. 1066–1073, 2017.

5. A. Ortiz, P.J. López, J. L. Luque, F. J. Martínez-Murcia, D. A. Aquino-Britez, J. Ortega, “An anomaly detection approach for dyslexia diagnosis using EEG signals”, J. M. F. Vicente, J. R. Álvarez-Sánchez, F. de la Paz, J. T. López, H. A. Moreo (eds.) Understanding the Brain Function and Emotions. LNCS, vol. 11486, pp. 369–378. Springer, Cham, 2019.