Application of neural networks and machine learning in network design

Fahmy, HI; Develekos, G; Douligeris, C

dc.contributor.author	Fahmy, HI	en
dc.contributor.author	Develekos, G	en
dc.contributor.author	Douligeris, C	en
dc.date.accessioned	2014-03-01T01:45:53Z
dc.date.available	2014-03-01T01:45:53Z
dc.date.issued	1997	en
dc.identifier.issn	07338716	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24774
dc.subject	Expert systems	en
dc.subject	Machine learning	en
dc.subject	Network design	en
dc.subject	Neural networks	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Computer simulation	en
dc.subject.other	Expert systems	en
dc.subject.other	Interactive computer systems	en
dc.subject.other	Knowledge acquisition	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Learning systems	en
dc.subject.other	Neural networks	en
dc.subject.other	Expert network designer (END)	en
dc.subject.other	Computer networks	en
dc.title	Application of neural networks and machine learning in network design	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/49.552072	en
heal.identifier.secondary	http://dx.doi.org/10.1109/49.552072	en
heal.publicationDate	1997	en
heal.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. In this paper, we present a neural network/knowledge acquisition machine-learning approach to improve 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.	en
heal.journalName	IEEE Journal on Selected Areas in Communications	en
dc.identifier.doi	10.1109/49.552072	en
dc.identifier.volume	15	en
dc.identifier.issue	2	en
dc.identifier.spage	226	en
dc.identifier.epage	237	en