Open AccessEvaluation of the Performance of Telecommunication Systems by Approach of Hybrid Stochastic Automata Combined With Neuro-Fuzzy Networks
Author(s) -
Florence Offole,
Atangana Ateba,
Timothee Kombe,
Fohoue Kennedy
Publication year - 2017
Publication title -
european scientific journal
Language(s) - English
Resource type - Journals
eISSN - 1857-7881
pISSN - 1857-7431
DOI - 10.19044/esj.2017.v13n18p498
Subject(s) - adaptive neuro fuzzy inference system , computer science , mode (computer interface) , reliability (semiconductor) , fuzzy logic , automaton , matlab , neuro fuzzy , artificial neural network , hybrid system , reliability engineering , real time computing , distributed computing , fuzzy control system , artificial intelligence , machine learning , engineering , operating system , power (physics) , physics , quantum mechanics
This paper presents a functional and dysfunctional behavioral study of a telecommunication system, with the aim to evaluate the performance of its constituent units. It is question of taking advantage offered by artificial intelligence in order to evaluate by modeling and simulation in system reliability. The methodological approach consists in combining ANFIS neuro-fuzzy networks with hybrid stochastic automata. The Neuro-Fuzzy ANFIS networks provide a prediction for the passage from nominal mode to degraded mode, by controlling the occurrence of malfunctions at transient levels. This allows to anticipate the occurrence of events degrading system performance, such as failures and disturbances. The objective is to maintain the system in nominal operating mode and prevent its tipping in degraded mode. The results are implanted around a demonstrator based on Scilab, and implemented on Matlab / Simulink.