Anomaly Detection in a Combined Driving System based on Unsupervised Learning-Reference-Cited by-同舟云学术

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Anomaly Detection in a Combined Driving System based on Unsupervised Learning

Published:2023-11-01 Issue:11 Volume:40 Page:921-928
ISSN:1225-9071
Container-title:Journal of the Korean Society for Precision Engineering
language:en
Short-container-title:KSPE

Author:

Park Kichang,Lee Yongkwan^ORCID

Funder

Ministry of SMEs and Startups

Ministry of Science and ICT

Institute for Information and communication Technology Planning and evaluation

Publisher

Korean Society of Precision Engineering

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Safety, Risk, Reliability and Quality

Reference20 articles.

1. Industrial Big Data in an Industry 4.0 Environment: Challenges, Schemes, and Applications for Predictive Maintenance

2. Predictive Maintenance in Industry 4.0: Current Themes

3. Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

4. Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0

5. A Review: Condition Based Techniques and Predictive Maintenance for Motor

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