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https://hdl.handle.net/1959.11/61883
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhang, Haoxi | en |
dc.contributor.author | Sanin, Cesar | en |
dc.contributor.author | Szczerbicki, Edward | en |
dc.date.accessioned | 2024-08-01T08:05:25Z | - |
dc.date.available | 2024-08-01T08:05:25Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Cybernetics and Systems, 47(1-2), p. 140-148 | en |
dc.identifier.issn | 1087-6553 | en |
dc.identifier.issn | 0196-9722 | en |
dc.identifier.uri | https://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.language | en | en |
dc.publisher | Taylor & Francis Inc | en |
dc.relation.ispartof | Cybernetics and Systems | en |
dc.title | When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1080/01969722.2016.1128776 | en |
local.contributor.firstname | Haoxi | en |
local.contributor.firstname | Cesar | en |
local.contributor.firstname | Edward | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | cmaldon3@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 140 | en |
local.format.endpage | 148 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 47 | en |
local.identifier.issue | 1-2 | en |
local.title.subtitle | A Promising New Perspective for Knowledge Representation and Sharing | en |
local.contributor.lastname | Zhang | en |
local.contributor.lastname | Sanin | en |
local.contributor.lastname | Szczerbicki | en |
dc.identifier.staff | une-id:cmaldon3 | en |
local.profile.orcid | 0000-0001-8515-417X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/61883 | en |
local.date.onlineversion | 2016-02-09 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | When Neural Networks Meet Decisional DNA | en |
local.relation.fundingsourcenote | This work was supported as part of the Project KYTZ201422 by the Scientific Research Foundation of CUIT. | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Zhang, Haoxi | en |
local.search.author | Sanin, Cesar | en |
local.search.author | Szczerbicki, Edward | en |
local.uneassociation | No | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.available | 2016 | en |
local.year.published | 2016 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/39f3db7c-f71c-4442-8e51-65d3c5fb10a4 | en |
local.subject.for2020 | 4602 Artificial intelligence | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.date.moved | 2024-08-02 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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