Intelligent methods for simulation in ATM networks

Abstract

The paper presents results from a number of investigations into the problems of implementing intelligent methods in the prediction and simulation of ATM traffic, based on time series and state models. A prognosis method based on a neuro-fuzzy model and learning vector quantization (LVQ) is suggested The implementation for stochastic and long range dependence source models is shown.