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Accurate Prediction of Quality of Transmission Based on a Dynamically Configurable Optical Impairment Model.

, , , , , , , , and . JOCN, 10 (1): A102-A109 (2018)

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Innovative Optical Networking by Optical Performance Monitoring and Learning Process., , , , , , , , , and . ECOC, page 1-3. IEEE, (2018)Accurate Prediction of Quality of Transmission Based on a Dynamically Configurable Optical Impairment Model., , , , , , , , and . JOCN, 10 (1): A102-A109 (2018)Network Capacity Improvement by Quality of Transmission Estimator with Learning Process., , , , , and . ECOC, page 1-3. IEEE, (2017)Q-availability based Virtual Optical Network Provisioning., , , , , , and . OFC, page 1-3. IEEE, (2018)Demonstration of Continuous Improvement in Open Optical Network Design by QoT Prediction using Machine Learning., , , , , , and . OFC, page 1-3. IEEE, (2019)Accurate prediction of quality of transmission with dynamically configurable optical impairment model., , , , , , , , and . OFC, page 1-3. IEEE, (2017)Reachability matrix and directed search-based optical path computation for large optical networks., , , and . ECOC, page 1-3. IEEE, (2014)Towards vendor-agnostic real-time optical network design with extended Kalman state estimation and recurrent neural network machine learning Invited., , , , and . JOCN, 13 (4): B21-B34 (2021)