Detecting Anomalous Multivariate Time-Series via Hybrid Machine Learning-Reference-Cited by-同舟云学术

Detecting Anomalous Multivariate Time-Series via Hybrid Machine Learning

Author:

Terbuch Anika¹^ORCID,O'Leary Paul¹^ORCID,Khalili-Motlagh-Kasmaei Negin¹^ORCID,Auer Peter²^ORCID,Zohrer Alexander³^ORCID,Winter Vincent³^ORCID

Affiliation:

1. Department of Product Engineering, Chair of Automation, Montanuniversität Leoben, Leoben, Austria

2. Department Mathematics and Information Technology, Chair of Information Technology, Montanuniversität Leoben, Leoben, Austria

3. Keller Grundbau Ges.m.b.H., Vienna, Austria

Funder

COMET Program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)”

Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Labor and Economy

Austrian Research Promotion Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference56 articles.

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

3. Extended Rayleigh-Ritz Autoencoder with Distribution-Free Statistics;2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC);2024-05-20