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

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

doi:10.1109/MWSCAS.1991.252104

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 proceeding › Conference 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 language	English
Title of host publication	1991 Proceedings of the 34th Midwest Symposium on Circuits and Systems, MWSCAS 1991
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	541-544
Number of pages	4
ISBN (Electronic)	0780306201
DOIs	https://doi.org/10.1109/MWSCAS.1991.252104
Publication status	Published - 1991
Externally published	Yes
Event	34th Midwest Symposium on Circuits and Systems, MWSCAS 1991 - Monterey, United States Duration: 1992 May 14 → 1992 May 17

Publication series

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

Conference

Conference	34th Midwest Symposium on Circuits and Systems, MWSCAS 1991
Country/Territory	United States
City	Monterey
Period	92/5/14 → 92/5/17

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/MWSCAS.1991.252104

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

A hybrid neural expert system for traffic estimation and failure detection in communication networks. / Lo, Z. P.; Kang, C.; Bavarian, B. et al.

1991 Proceedings of the 34th Midwest Symposium on Circuits and Systems, MWSCAS 1991. Institute of Electrical and Electronics Engineers Inc., 1991. p. 541-544 252104 (Midwest Symposium on Circuits and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lo, ZP, 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., 252104, Midwest Symposium on Circuits and Systems, Institute of Electrical and Electronics Engineers Inc., pp. 541-544, 34th Midwest Symposium on Circuits and Systems, MWSCAS 1991, Monterey, United States, 92/5/14. https://doi.org/10.1109/MWSCAS.1991.252104

Lo ZP, Kang C, Bavarian B, Tan H. 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. Institute of Electrical and Electronics Engineers Inc. 1991. p. 541-544. 252104. (Midwest Symposium on Circuits and Systems). doi: 10.1109/MWSCAS.1991.252104

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author = "Lo, {Z. P.} and C. Kang and B. Bavarian and H. Tan",

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AB - 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.

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ER -

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

Abstract

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ASJC Scopus subject areas

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