2021-12-102021-12-102009-03Hacıismailoğlu, M. C. vd. (2009). "Prediction of dynamic hysteresis loops of nano-crystalline cores". Expert Systems with Applications, 36(2), Part 1, 2225-2227.0957-4174https://doi.org/10.1016/j.eswa.2007.12.051https://www.sciencedirect.com/science/article/pii/S0957417407006422http://hdl.handle.net/11452/23167Dynamic hysteresis loops of a range of nano-crystalline cores have been obtained over a wide frequency range (1-50 kHz). A dynamic hysteresis model front measurements using an artificial neural network trained by the delta-bar-delta learning algorithm has been developed. The input parameters include the geometrical dimensions of cores, peak magnetic induction and magnetizing frequency. The results show the neural network model has an acceptable estimation capability for dynamic hysteresis loops of toroidal nano-crystalline cores.eninfo:eu-repo/semantics/closedAccessDynamic hysteresis modellingNano-crystalline coresNeural networkToroidal coresComputer scienceEngineeringOperations research & management scienceCrystalline materialsHysteresis loopsMagnetic levitation vehiclesMagnetic materialsNeural networksDelta-bar-deltaDynamic hysteresis loopsDynamic hysteresis modelingDynamic hysteresis modellingGeometrical dimensionsNanocrystalline coresNeural network modelWide frequency rangeHysteresisArticle0002621780001222-s2.0-5634916525222252227362, Part 1Computer science, artificial intelligenceEngineering, electrical & electronicOperations research & management scienceSilicon Steel; Soft Magnetic Materials; Induction Motors