Detecting Anomalies in the Optical Layer Using Unsupervised Machine Learning
Paper in proceeding, 2024
We propose an unsupervised machine learning (ML) approach using field data for the detection of optical layer anomalies. We show how multivariate ML models can forecast hard failures by detecting soft failures.
Author
Sandra Aladin
École de Technologie Supérieure (ÉTS)
Student at Chalmers
Lena Wosinska
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Christine Tremblay
École de Technologie Supérieure (ÉTS)
2024 Optical Fiber Communications Conference and Exhibition, OFC 2024 - Proceedings
9781957171326 (ISBN)
2024 Optical Fiber Communications Conference and Exhibition, OFC 2024
San Diego, USA,
San Diego, USA,
Subject Categories
Computer Science
DOI
10.1364/ofc.2024.th3i.4
ISBN
9781957171326