Use of Fuzzy Neural Networks in Identification of the State of Data Transmission System Elements
- 10.2991/aisr.k.201029.010How to use a DOI?
- direct distribution neural network, fuzzy neural network, forecasting, data transmission system, expert methods, uncertainty
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.
- © 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/).
Cite this article
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 -