Application of neural networks and machine learning in network design

Author

Fahmy, Hany I. ; Develekos, George ; Doulige, Christos

Author_Institution

Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA

Volume

15

Issue

2

fYear

1997

fDate

2/1/1997 12:00:00 AM

Firstpage

226

Lastpage

237

Abstract

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END´s efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies

Keywords

computer networks; digital simulation; expert systems; knowledge representation; learning (artificial intelligence); neural nets; simulation; affordable networks; artificial intelligence tools; communication network design; expert network designer; knowledge representation tools; large structured computer network; machine learning; network configuring; network evaluation; network modeling; network simulation tools; networking technologies; neural networks; reliable networks; technology specifications updating; Application software; Artificial intelligence; Artificial neural networks; Communication networks; Computational modeling; Computer network reliability; Computer simulation; Machine learning; Neural networks; Telecommunication network reliability;

fLanguage

English

Journal_Title

Selected Areas in Communications, IEEE Journal on

Publisher

ieee

ISSN

0733-8716

Type

jour

DOI

10.1109/49.552072

Filename

552072