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dc.contributor.authorPensuwon, W.
dc.contributor.authorAdams, R.G.
dc.contributor.authorDavey, N.
dc.date.accessioned2011-10-18T15:01:08Z
dc.date.available2011-10-18T15:01:08Z
dc.date.issued2000
dc.identifier.citationPensuwon , W , Adams , R G & Davey , N 2000 , Optimising a neural tree classifier using a genetic algorithm . in Proceedings of the 4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies (KES'2000) . vol. 2 , pp. 848-851 .
dc.identifier.isbn0780364007
dc.identifier.otherPURE: 422484
dc.identifier.otherPURE UUID: bb8e8f66-dc4b-4376-a88e-ce02d9689f7a
dc.identifier.otherdspace: 2299/831
dc.identifier.urihttp://hdl.handle.net/2299/6718
dc.description.abstractThis paper documents experiments performed using a GA to optimise the parameters of a dynamic neural tree model. Two fitness functions were created from two selected clustering measures, and a population of genotypes, specifying parameters of the model were evolved. This process mirrors genomic evolution and ontogeny. It is shown that the evolved parameter values improved performanceen
dc.language.isoeng
dc.relation.ispartofProceedings of the 4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies (KES'2000)
dc.rightsOpen
dc.titleOptimising a neural tree classifier using a genetic algorithmen
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionSchool of Computer Science
dc.relation.schoolSchool of Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2000
rioxxterms.versionAM
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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