1. Açık Erişim@BUU
  2. İndeksli Yayınlar
  3. Web of Science
Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/25915
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dc.date.accessioned2022-04-21T05:49:35Z-
dc.date.available2022-04-21T05:49:35Z-
dc.date.issued2003-
dc.identifier.citationÖztürk, N. (2003). “Use of genetic algorithm to design optimal neural network structure”. Engineering Computations, 20(7-8), 979-997.en_US
dc.identifier.issn0264-4401-
dc.identifier.urihttps://doi.org/10.1108/02644400310502982-
dc.identifier.urihttps://www.emerald.com/insight/content/doi/10.1108/02644400310502982/full/html-
dc.identifier.urihttp://hdl.handle.net/11452/25915-
dc.description.abstractIn this research, neural network (NN) and genetic algorithm (GA) are used together to design optimal NN structure. The proposed approach combines the characteristics of GA and NN to reduce the computational complexity of artificial intelligence applications in design and manufacturing. Genetic input selection approach is introduced to obtain optimal NN topology. Experimental results are given to evaluate the performance of the proposed system.en_US
dc.language.isoenen_US
dc.publisherEmerald Group Publishingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComputer scienceen_US
dc.subjectEngineeringen_US
dc.subjectMathematicsen_US
dc.subjectMechanicsen_US
dc.subjectMathematical modellingen_US
dc.subjectProgramming and algorithm theoryen_US
dc.subjectNeural netsen_US
dc.subjectFeature recognitionen_US
dc.subjectManufacturing featuresen_US
dc.subjectOptimizationen_US
dc.subjectSearchen_US
dc.subjectClassificationen_US
dc.subjectSystemen_US
dc.subjectModelsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectBackpropagationen_US
dc.subjectComputational complexityen_US
dc.subjectDesignen_US
dc.subjectFeature extractionen_US
dc.subjectLearning systemsen_US
dc.subjectManufactureen_US
dc.subjectMathematical modelsen_US
dc.subjectMathematical programmingen_US
dc.subjectMultilayer neural networksen_US
dc.subjectGenetic input selection methoden_US
dc.subjectNeural network structureen_US
dc.subjectGenetic algorithmsen_US
dc.titleUse of genetic algorithm to design optimal neural network structureen_US
dc.typeArticleen_US
dc.identifier.wos000223976000009tr_TR
dc.identifier.scopus2-s2.0-17344381470tr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.tr_TR
dc.identifier.startpage979tr_TR
dc.identifier.endpage997tr_TR
dc.identifier.volume20tr_TR
dc.identifier.issue7-8tr_TR
dc.relation.journalEngineering Computationsen_US
dc.contributor.buuauthorÖztürk, Nursel-
dc.contributor.researcheridAAG-9336-2021tr_TR
dc.subject.wosComputer science, interdisciplinary applicationsen_US
dc.subject.wosEngineering, multidisciplinaryen_US
dc.subject.wosMathematics, interdisciplinary applicationsen_US
dc.subject.wosMechanicsen_US
dc.indexed.wosSCIEen_US
dc.indexed.scopusScopusen_US
dc.wos.quartileQ3en_US
dc.wos.quartileQ2 (Engineering, multidisciplinary)en_US
dc.contributor.scopusid7005688805tr_TR
dc.subject.scopusComputer Aided Manufacturing; Feature Recognition; Machiningen_US
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