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

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dc.contributor.advisorChan, H Anthonyen_ZA
dc.contributor.authorLi, Yangen_ZA
dc.date.accessioned2014-07-31T10:55:09Z
dc.date.available2014-07-31T10:55:09Z
dc.date.issued2007en_ZA
dc.descriptionIncludes abstract.
dc.descriptionIncludes bibliographical references (leaves 251-257).
dc.description.abstractIn 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.en_ZA
dc.identifier.apacitationLi, Y. (2007). <i>Applying human-like intelligence to future generation network to improve communication efficiency</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/5183en_ZA
dc.identifier.chicagocitationLi, Yang. <i>"Applying human-like intelligence to future generation network to improve communication efficiency."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2007. http://hdl.handle.net/11427/5183en_ZA
dc.identifier.citationLi, Y. 2007. Applying human-like intelligence to future generation network to improve communication efficiency. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Li, Yang AB - 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. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - Applying human-like intelligence to future generation network to improve communication efficiency TI - Applying human-like intelligence to future generation network to improve communication efficiency UR - http://hdl.handle.net/11427/5183 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/5183
dc.identifier.vancouvercitationLi Y. Applying human-like intelligence to future generation network to improve communication efficiency. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/5183en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleApplying human-like intelligence to future generation network to improve communication efficiencyen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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