Deep Learning for Multi-Step Performance Prediction in Operational Optical Networks

Ameni Mezni; Douglas W. Charlton; Christine Tremblay; Christian Desrosiers

doi:10.1364/CLEO_SI.2020.STh4M.1

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2020),
paper STh4M.1
•https://doi.org/10.1364/CLEO_SI.2020.STh4M.1

Deep Learning for Multi-Step Performance Prediction in Operational Optical Networks

Ameni Mezni, Douglas W. Charlton, Christine Tremblay, and Christian Desrosiers

CLEO: Science and Innovations 2020

Washington, DC United States
10–15 May 2020
ISBN: 978-1-943580-76-7

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Applications of Machine Learning (STh4M)

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A. Mezni, D. W. Charlton, C. Tremblay, and C. Desrosiers, "Deep Learning for Multi-Step Performance Prediction in Operational Optical Networks," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2020), paper STh4M.1.

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Abstract

We propose a 1D Convolutional Neural Network to predict the performance of a lightpath using field bit error rate data and we evaluate the model robustness over forecast horizons up to 24 hours.

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