Using Modern Architectures of Recurrent Neural Networks for Technical Diagnosis of Complex Systems

Abstract

The paper provides an overview of modern recurrent neural network architectures that can be used as a model (building tool) for diagnosis and predicting of infocommunication systems elements. The paper presents arguments in favor of the using of recurrent neural networks. Also, to determine the best architecture, were conducted a number of experiments, and on the basis of the results, conclusions were made about the future prospects of using modern architecture.