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

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.

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