A hybrid neural expert system for traffic estimation and failure detection in communication networks

Z. P. Lo, C. Kang, B. Bavarian, H. Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses a new methodology to estimate user traffic demand and to detect topological changes in a large scale communication network by using a hybrid neural expert system. We develop a framework of hierarchical acquisition and estimation using multiple supervised learning neural network modules augmented in a distributed tree structure. This paper discusses the new system development approach and subsequent simulation results.

Original languageEnglish
Title of host publication1991 Proceedings of the 34th Midwest Symposium on Circuits and Systems, MWSCAS 1991
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages541-544
Number of pages4
ISBN (Electronic)0780306201
DOIs
Publication statusPublished - 1991 Jan 1
Externally publishedYes
Event34th Midwest Symposium on Circuits and Systems, MWSCAS 1991 - Monterey, United States
Duration: 1992 May 141992 May 17

Publication series

NameMidwest Symposium on Circuits and Systems
ISSN (Print)1548-3746

Conference

Conference34th Midwest Symposium on Circuits and Systems, MWSCAS 1991
CountryUnited States
CityMonterey
Period92/5/1492/5/17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Cite this

Lo, Z. P., Kang, C., Bavarian, B., & Tan, H. (1991). A hybrid neural expert system for traffic estimation and failure detection in communication networks. In 1991 Proceedings of the 34th Midwest Symposium on Circuits and Systems, MWSCAS 1991 (pp. 541-544). [252104] (Midwest Symposium on Circuits and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MWSCAS.1991.252104