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Department of Electrical Engineering

Applying human-like intelligence to future generation network to improve communication efficiency

Abstract

dc:description.abstract

In recent decades, communications network has evolved at drastic speed to provide advanced and intelligent services. This strengthening service provision owes to the successful establishment of various intelligent networks and the use of artificial intelligence, pervasive computing, and social networking in communications. It has consequently endowed network users with abundant choices of communication services. While these communications services are bringing convenience to human lives, people in turn are performing more tasks. The current network with its large number of available communications services is then often burdening network users with the complexity and inflexibility in using these services. In particular, the network lacks the initiative and the ability to investigate a user’s most recent communication needs and subsequently adjust the manner of service provision according to these needs and user connecting possibilities. The network needs to be more intelligent to handle these problems. We therefore propose importing human-like intelligence into the network to facilitate communication-session processing according to user needs.

Degree

thesis:*
Grantor dc:publisher.institution
Department of Electrical Engineering
Year dc:date.issued
2007

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Li, Yang
Advisor dc:contributor.advisor
  • Chan, H Anthony

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/5183
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/5183

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Li, Yang. Applying human-like intelligence to future generation network to improve communication efficiency. Department of Electrical Engineering, 2007. http://hdl.handle.net/11427/5183