Artificial neural networks approach to the non-linear analysis of rectangular plates

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dc.contributor.authorCivalek, Ömer
dc.contributor.authorÜlker, Mehmet
dc.date.accessioned2026-08-12T16:12:59Z
dc.date.issued2004
dc.departmentFırat Üniversitesi
dc.description.abstractThe linear and non-linear analysis of rectangular plates has been presented via artificial intelligence techniques and numerical examples are solved by means of the developed program. The back-propagation neural network has been used in the solution. The thickness of plates has been normalized by the use of the fuzzy triangular membership function. The center point moments and deflection have been obtained for the numerical applications. It has been emphasized that the artificial intelligence technique is an alternative method that can be used in structural engineering.
dc.identifier.endpage3190
dc.identifier.issn1300-3453
dc.identifier.issue2
dc.identifier.scopus2-s2.0-4644326695
dc.identifier.scopusqualityN/A
dc.identifier.startpage3171
dc.identifier.urihttps://hdl.handle.net/11508/42785
dc.identifier.volume15
dc.indekslendigikaynakScopus
dc.language.isotr
dc.relation.ispartofTeknik Dergi/Technical Journal of Turkish Chamber of Civil Engineers
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectArtificial intelligence; Backpropagation; Deflection (structures); Fuzzy sets; Membership functions; Neural networks; Nonlinear systems; Structural analysis; Structural design; Fuzzy triangular membership functions; Non-linear analysis; Rectangular plates; Plates (structural components)
dc.titleArtificial neural networks approach to the non-linear analysis of rectangular plates
dc.title.alternativeDikdörtgen Plaklarin Do?rusal Olmayan Analizinde Yapay Sinir A?i Yaklaşimi
dc.typeArticle

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