Machine-Learning-Based Soft-Failure Detection and Identification in Optical Networks

Abstract

We develop and test several machine-learning methods to perform detection and identification of equipment failures in optical networks. Results, obtained over real BER traces, show above 98% accuracy in most cases with reasonable algorithm complexity.