Machine-Learning-Based Lightpath QoT Estimation and Forescasting

Machine learning (ML) is more and used to address the challenges of managing physical layer increasingly heterogeneous complex optical networks. In this tutorial, we illustrate how simple sophisticated machine methods can be in lightpath quality transmission (QoT) estimation forecast tasks. We also discuss data processing strategies with aim determine relevant features feed ML classifiers predictors. then introduce a preliminary study on application transfer try overcome scarcity field data.