Metamodelling of Queuing Systems using Fuzzy Graphs

Authors

  • G. Lauks Riga Technical University
  • J. Jeļinskis Riga Technical University

Abstract

The dynamic behavior of queuing systems under sophisticated traffic can be analyzed using simulation models. Unfortunately, often the results are only available in a form of large datasets, which makes it hard to extract the underlying regularities. One of the interesting applications is the approximation of the behavior of simulation models, called metamodelling. The goal of this paper is to approximate the behavior of queuing systems as well as to extract some understandable knowledge about the simulation model. In this paper we present the knowledge extraction from trained Neural Networks. The underlying knowledge can be extracted from the Network in form of a Fuzzy Graph. The Fuzzy Graphs are generated using Rectangular Basis Functions of Neural Networks. The research results are illustrated with a range of experiments performed. Ill. 1, bibl. 8 (in English; summaries in English, Russian and Lithuanian).

Downloads

Published

2009-04-19

How to Cite

Lauks, G., & Jeļinskis, J. (2009). Metamodelling of Queuing Systems using Fuzzy Graphs. Elektronika Ir Elektrotechnika, 92(4), 61-54. Retrieved from https://eejournal.ktu.lt/index.php/elt/article/view/10246

Issue

Section

T 180 TELECOMMUNICATION ENGINEERING