A Hybrid Machine-Learning Ensemble for Anomaly Detection in Real-Time Industry 4.0 Systems-Reference-Cited by-同舟云学术

A Hybrid Machine-Learning Ensemble for Anomaly Detection in Real-Time Industry 4.0 Systems

Published:2022 Issue: Volume:10 Page:72024-72036
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Velasquez David¹^ORCID,Perez Enrique²,Oregui Xabier²,Artetxe Arkaitz²^ORCID,Manteca Jorge³,Mansilla Jordi Escayola⁴,Toro Mauricio¹,Maiza Mikel²,Sierra Basilio⁵^ORCID

Affiliation:

1. RID on Information Technologies and Communications Research Group, Universidad EAFIT, Medellín, Colombia

2. Department of Data Intelligence for Energy and Industrial Processes, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain

3. Technical Department Direction, Mapner, Astigarraga, Spain

4. Department of Statistics and Operational Research, Universitat Oberta de Catalunya, Rambla del Poblenou, Barcelona, Spain

5. Department of Computer Science and Artificial Intelligence, University of Basque Country (UPV/EHU), Donostia-San Sebastián, Spain

Funder

Vicomtech Foundation

Universidad EAFIT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09813703.pdf?arnumber=9813703

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