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

  1. Velasquez, D.
  2. Perez, E.
  3. Oregui, X.
  4. Artetxe, A.
  5. Manteca, J.
  6. Mansilla, J.E.
  7. Toro, M.
  8. Maiza, M.
  9. Sierra, B.
Revue:
IEEE Access

ISSN: 2169-3536

Année de publication: 2022

Volumen: 10

Pages: 72024-72036

Type: Article

DOI: 10.1109/ACCESS.2022.3188102 GOOGLE SCHOLAR lock_openAccès ouvert editor

Objectifs de Développement Durable