QoT Estimation for Unestablished Lighpaths using Machine Learning Page 1 Th1J.1.pdf
OFC 2017 © OSA 2017 QoT Estimation for Unestablished Lighpaths using Machine …

Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of
capital importance for an optimized design of optical networks. Due to the continuous …

How Uncertainty on the Fiber Span Lengths Influences QoT Estimation Using Machine
Learning in WDM Networks Page 1 Th3D.5.pdf OFC 2020 © OSA 2020 How Uncertainty on …

Cognitive Tool for Estimating the QoT of New Lightpaths Page 1 M3A.3.pdf OFC 2018 © OSA
2018 Cognitive Tool for Estimating the QoT of New Lightpaths Sandra Aladin, Christine …

Estimating the quality of transmission (QoT) of a candidate lightpath prior to its establishment
is of pivotal importance for effective decision making in resource allocation for optical …

Machine learning (ML) is more and more used to address the challenges of managing the
physical layer of increasingly heterogeneous and complex optical networks. In this tutorial …

Artificial intelligence (AI) and machine learning (ML) continue to demonstrate substantial
capabilities in solving a wide range of optical-network-related tasks such as fault …

Active vs Transfer Learning Approaches for QoT Estimation with Small Training Datasets
Page 1 M4E.1.pdf OFC 2020 © OSA 2020 Active vs Transfer Learning Approaches for QoT …

Estimating the quality of transmission (QoT) of a lightpath before its establishment is a critical
procedure for efficient design and management of optical networks. Recently, supervised …

Reliable and conservative computation of the quality of transmission (QoT) of transparent
lightpaths (LPs) is a crucial need for software-defined control and management of the …