Use of Fuzzy Neural Networks in Identification of the State of Data Transmission System Elements

DOI

10.2991/aisr.k.201029.010How to use a DOI?

Keywords

direct distribution neural network, fuzzy neural network, forecasting, data transmission system, expert methods, uncertainty

Abstract

The possibilities of using direct distribution neural networks with a different number of hidden layers and fuzzy neural networks in the process of identifying operational states of data transmission system elements are compared. As input, it is proposed to use the data collected by monitoring systems of the telecommunications network operator. It takes into account factors that are presented not only in quantitative, but also in qualitative forms, used to fill the knowledge base of a fuzzy neural network, which allows a more complete analysis of the elements of complex socio-technical systems. Automation of the analysis of the operational states of the elements of data transmission systems will allow not only to relieve highly qualified specialists from routine work and improve the quality of decisions on repair or modernization, but also to predict critical, pre-emergency conditions of elements that can reduce the performance of the data transmission network in time.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - A Aleksandr Oleinikov
AU  - Aleksandr Sorokin
AU  - Ilya Beresnev
PY  - 2020
DA  - 2020/11/10
TI  - Use of Fuzzy Neural Networks in Identification of the State of Data Transmission System Elements
BT  - Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
PB  - Atlantis Press
SP  - 48
EP  - 51
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.201029.010
DO  - 10.2991/aisr.k.201029.010
ID  - Oleinikov2020
ER  -