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dc.contributor.advisor | Engelbrecht, Andries P. | en |
dc.contributor.postgraduate | Nel, Gert M | en |
dc.date.accessioned | 2013-09-06T20:54:10Z | |
dc.date.available | 2005-06-09 | en |
dc.date.available | 2013-09-06T20:54:10Z | |
dc.date.created | 2005-01-04 | en |
dc.date.issued | 2006-06-09 | en |
dc.date.submitted | 2005-06-09 | en |
dc.description | Dissertation (MSc)--University of Pretoria, 2006. | en |
dc.description.abstract | Local search algorithms have been proved to be effective in refining solutions that have been found by other algorithms. Evolutionary algorithms, in particular global search algorithms, have shown to be successful in producing approximate solutions for optimisation and classification problems in acceptable computation times. A relatively new method, memetic algorithms, uses local search to refine the approximate solutions produced by global search algorithms. This thesis develops such a memetic algorithm. The global search algorithm used as part of the new memetic algorithm is a genetic program that implements the building block hypothesis by building simplistic decision trees representing valid solutions, and gradually increases the complexity of the trees. The specific building block hypothesis implementation is known as the building block approach to genetic programming, BGP. The effectiveness and efficiency of the new memetic algorithm, which combines the BGP algorithm with a local search algorithm, is demonstrated. | en |
dc.description.availability | unrestricted | en |
dc.description.department | Computer Science | en |
dc.identifier.citation | Nel, G 2005, A memetic genetic program for knowledge discovery, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/25350 > | en |
dc.identifier.upetdurl | http://upetd.up.ac.za/thesis/available/etd-06092005-091517/ | en |
dc.identifier.uri | http://hdl.handle.net/2263/25350 | |
dc.language.iso | en | |
dc.publisher | University of Pretoria | en_ZA |
dc.rights | © 2005, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. | en |
dc.subject | Global search | en |
dc.subject | Classification problems | en |
dc.subject | Optimisation | en |
dc.subject | Local search | en |
dc.subject | Genetic program | en |
dc.subject | Decision trees | en |
dc.subject | Bgp | en |
dc.subject | Mbgp. | en |
dc.subject | Building block hypothesis | en |
dc.subject | Memetic algorithms | en |
dc.subject | Evolutionary algorithms | en |
dc.subject | UCTD | en_US |
dc.title | A memetic genetic program for knowledge discovery | en |
dc.type | Dissertation | en |