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Demonstration of Continuous Improvement in Open Optical Network Design by QoT Prediction using Machine Learning

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Abstract

We demonstrate for the first time an interactive process with QoT prediction learning design server for multi-vendor optical networks using vendor-neutral optical model parameter learning from real BER measurements, enabling continuous improvement in network efficiency.

© 2019 The Author(s)

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