Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61883
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dc.contributor.authorZhang, Haoxien
dc.contributor.authorSanin, Cesaren
dc.contributor.authorSzczerbicki, Edwarden
dc.date.accessioned2024-08-01T08:05:25Z-
dc.date.available2024-08-01T08:05:25Z-
dc.date.issued2016-
dc.identifier.citationCybernetics and Systems, 47(1-2), p. 140-148en
dc.identifier.issn1087-6553en
dc.identifier.issn0196-9722en
dc.identifier.urihttps://hdl.handle.net/1959.11/61883-
dc.description.abstract<p>In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest neighbors), logistic regression, and AdaBoost in classification tasks, and the results show that our approach is very promising with regard to the enhancement of the accuracy of knowledge-based predictions required in complex decision-making problems.</p>en
dc.languageenen
dc.publisherTaylor & Francis Incen
dc.relation.ispartofCybernetics and Systemsen
dc.titleWhen Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharingen
dc.typeJournal Articleen
dc.identifier.doi10.1080/01969722.2016.1128776en
local.contributor.firstnameHaoxien
local.contributor.firstnameCesaren
local.contributor.firstnameEdwarden
local.profile.schoolSchool of Science and Technologyen
local.profile.emailcmaldon3@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeUnited States of Americaen
local.format.startpage140en
local.format.endpage148en
local.peerreviewedYesen
local.identifier.volume47en
local.identifier.issue1-2en
local.title.subtitleA Promising New Perspective for Knowledge Representation and Sharingen
local.contributor.lastnameZhangen
local.contributor.lastnameSaninen
local.contributor.lastnameSzczerbickien
dc.identifier.staffune-id:cmaldon3en
local.profile.orcid0000-0001-8515-417Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61883en
local.date.onlineversion2016-02-09-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleWhen Neural Networks Meet Decisional DNAen
local.relation.fundingsourcenoteThis work was supported as part of the Project KYTZ201422 by the Scientific Research Foundation of CUIT.en
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorZhang, Haoxien
local.search.authorSanin, Cesaren
local.search.authorSzczerbicki, Edwarden
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.available2016en
local.year.published2016en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/39f3db7c-f71c-4442-8e51-65d3c5fb10a4en
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-08-02en
Appears in Collections:Journal Article
School of Science and Technology
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