… the application of ML to optical networking. Specifically, the … and on their application in the
optical networks field, and ii) we … the areas of optical communication and optical networking to …

… Paradigms and motivations of applying machine learning in optical networks This section
summarizes the paradigms of applying machine learning in solving optical network problems. …

… optical networks to avoid service disruptions and to satisfy customers’ service level agreements.
Machine learning … which failure management in optical networks has been traditionally …

… networks that improve the user experience. This paper performs a systematic mapping that
provides an overview of machine learning in optical networks… of machine learning techniques …

… importance for optical network operators, … machine learning methods to estimate the QoT
of optical channels. It is noted that ML has been already used to address the problem of optical …

… Based on software-defined optical networks (SDON) [11], Self-Optimizing Optical Networks
(… to improve performance of network management by introducing ML into optical networks. To …

… machine learning in optical networks. At first, we briefly introduce the routing and wavelength
allocation (RWA) problem in WDM optical networks, … in SDM optical networks respectively. …

… In conclusion, neural networks and machine learning in general are not intended to solve
NP-complete problems like the RWA ILP. However, ML algorithms are effective techniques for …

… optical network automation include the work in [11] that, similar to [10], presents an overview
on the application of machine learning techniques in optical networks (… in optical networking. …

… make better use of network resources and reduce margins. … on software defined optical
network (SDON), machine learning (ML… Firstly, we elaborate the QoT problem in optical networks, …