Miti, G.K.Moses, Anthony JohnFox, David2022-03-232022-03-232003-01Miti, G. K. vd. (2003). “A neural network-based tool for magnetic performance prediction of toroidal cores”. Journal of Magnetism and Magnetic Materials, 254(Special Issue), 262-264.0304-8853https://doi.org/10.1016/S0304-8853(02)00788-6http://hdl.handle.net/11452/25292Bu çalışma, 05-07 Eylül 2001 tarihleri arasında Bilbao[İspanya]’da düzenlenen 15. International Symposium on Soft Magnetic Materials’da bildiri olarak sunulmuştur.Geometrical and building parameters have a strong influence on magnetic performance of wound toroidal cores made from electrical steel or similar strip products. This paper presents a neural network-based approach to predict losses and permeability in such cores of varying geometries over an induction range of 0.2-1.8T (50Hz). The approach is shown to be successful.eninfo:eu-repo/semantics/closedAccessMaterials sciencePhysicsArtificial intelligenceMagnetic lossesNeural networksSoft magnetic materialsStrip-wound coresMagnetic leakageMagnetic permeabilityToroidal coresMagnetic coresArticle0001800756000812-s2.0-0037211428262264254Special IssueMaterials science, multidisciplinaryPhysics, condensed matterSilicon Steel; Soft Magnetic Materials; Iron