Intelligent methods for simulation in ATM networks

Author

Radev, Dimitar ; Radeva, Svetla

Author_Institution

Dept. of Commun. Technique & Technol., Univ. of Rousse, Bulgaria

fYear

2003

fDate

26-28 Oct. 2003

Firstpage

90

Lastpage

93

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.

Keywords

asynchronous transfer mode; digital simulation; fuzzy logic; fuzzy neural nets; learning (artificial intelligence); perceptrons; prediction theory; stochastic processes; telecommunication computing; telecommunication traffic; time series; vector quantisation; ATM networks; ATM traffic; fuzzy logic; intelligent methods; layered perceptron; learning vector quantization; long range dependence source; neuro-fuzzy model; state models; stochastic source; time series; Asynchronous transfer mode; Chaos; Computational modeling; Fuzzy logic; Fuzzy sets; Intelligent networks; Predictive models; Stochastic processes; Telecommunication traffic; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Mobile Future and Symposium on Trends in Communications, 2003. SympoTIC '03. Joint First Workshop on

Print_ISBN

0-7803-7993-4

Type

conf

DOI

10.1109/TIC.2003.1249096

Filename

1249096