Advanced Applications of Machine Learning Techniques in FOITS

The use of machine learning methods in fiberoptic information transmission systems (FOITS) is considered. The article discusses the basic operating principles of fiber optic systems and the problems they face, such as noise, nonlinear effects, and degradation of transmitted information. Describes various machine learning techniques used in fiber optic communication systems to control and monitor performance, prevent intelligent decisions, and suppress nonlinear fiber optic noise. Approaches used in machine learning are presented, such as neural networks, classification and regression algorithms, their application in the analysis and optimization of fiber optic systems, such as neural networks, support vector machines, classification and regression algorithms, their application in the analysis and optimization of fiber optic systems. This paper proposes a method for monitoring performance and predicting failures in optical networks based on machine learning.

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