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Application of Artificial Neural Networks in the Prediction of Critical

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dc.contributor.author Ibrikci, T
dc.contributor.author Sacma, S
dc.contributor.author Yildirim, V
dc.contributor.author Koca, T
dc.date.accessioned 2022-10-19T08:16:27Z
dc.date.available 2022-10-19T08:16:27Z
dc.date.issued 2010
dc.identifier.uri http://hdl.handle.net/11616/82006
dc.description.abstract This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. (C)2010 Journal of Mechanical Engineering. All rights reserved.
dc.description.abstract C1 [Ibrikci, Turgay] Cukurova Univ, Elect Elect Engn Dept, Adana, Turkey.
dc.description.abstract [Sacma, Selim; Yildirim, Vebil] Cukurova Univ, Dept Mech Engn, Adana, Turkey.
dc.description.abstract [Koca, Tarkan] Univ Inonu, Arapgir Vocat Sch, Malatya, Turkey.
dc.source STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
dc.title Application of Artificial Neural Networks in the Prediction of Critical
dc.title Buckling Loads of Helical Compression Springs


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