ARTIFICIAL INTELLIGENCE MODELLING OF STOCHASTIC PROCESSES IN DIGITAL COMMUNICATION NETWORKS
Dimitar Radev - Svetla Radeva
The paper presents results from a number of investigations into the problems of implementation of
Intelligent methods in prediction and simulation of the ATM traffic, based on time series and state
models. The prognoses based on neuro-fuzzy model and Learning Vector Quantization (LVQ) is suggested.
The implementation for the stochastic and long range dependence source models is shown.
Keywords: digital communications, queuing networks, quality of service (QoS), artificial intelligence methods, learning vector quantization (LVQ)