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CURRENT MEMBERS

Below is a list of the doctorate members actively conducting research at CIRG. Click on each name for more detailed information on the researcher and his/her project.


M Snyman

PhD Started in 2009

P Raharja

PhD Started in 2009

M Mtshali

PhD Started in 2009

B Kalema

PhD Started in 2009

J Grobler

PhD Started in 2009
M.Eng Completed in 2009

M Ahmad

PhD Started in 2009

T Museba

PhD Started in 2008

L Li

PhD Started in 2008

C Naicker

PhD Started in 2007
M.Sc Completed in 2006
Hons-B.Sc Completed in 2002

K Malan

PhD Started in 2007

M Greeff

PhD Started in 2007

B Baridam

PhD Started in 2007

MC du Plessis

PhD Started in 2006

D Constantinou

PhD Started in 2006

A Graaff

PhD Started in 2005
M.Sc Completed in 2003

N Franken

PhD Started in 2005
M.Sc Completed in 2004
Hons-B.Sc Completed in 2002

A Ismail

PhD Started in 2005
M.Sc Completed in 2001

ALUMNI

Below is a list of previous doctorate members that conducted research at CIRG. Click on each name for more detailed information on the researcher and his/her project.


L Schoeman

PhD Completed in 2010

P Lutu

PhD Completed in 2010

S Khan

PhD Completed in 2009

D Rodic

PhD Completed in 2005
M.Sc Completed in 1999

M Omran

PhD Completed in 2005

F van den Bergh

PhD Completed in 2002

MEMBER PROFILE



 Name:

 Attie Graaff

Portrait photo

 E-mail:

 agraaff@cs.up.ac.za

 Group(s):

 Artificial Immune Systems

 

 Degree specific information: PhD

 Title:

 Artificial Immune Network Systems for Clustering Dynamically Changing Data

 Abstract:

Not Available

 Supervisor / Co-Supervisor:

 AP Engelbrecht

 Thesis:

 Not available for download yet.

 

 Degree specific information: M.Sc

 Title:

 The Artificial Immune System with Evolved Lymphocytes

 Abstract:

The natural immune system can be modeled into an artificial immune system that can be used to detect any unwanted patterns in a non-biological environment. One of the main tasks of an immune system is to learn the structure of these unwanted patterns for a faster response to future foreign patterns with the same or similar structure. The artificial immune system (AIS) can therefor be seen as a pattern recognition system. The AIS contains artificial lymphocytes (ALC) that classify any pattern either as part of a predetermined set of patterns or not. It is possible for an ALC to classify more than one pattern and even classify a pattern better than other ALCs. The ALCs that never classify any pattern need to be replaced by newly created or evolved ALCs. It is therefore important to know what ALCs need to be replaced so that ALCs with a better classification are kept. In the natural immune system the lymphocytes have different states: Immature, Mature, Memory or Annihilated. Lymphocytes in the annihilated state needs to be replaced by newly created or evolved lymphocytes. The thesis presents an AIS for detection of unwanted patterns and proposes a threshold function to determine the state of an ALC.

 Supervisor / Co-Supervisor:

 AP Engelbrecht

 Thesis:

 Download




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