6533b829fe1ef96bd128ae0d

RESEARCH PRODUCT

Identification of parameters of the Jiles-Atherton model by neural networks

Marco Trapanense

subject

Identification (information)HysteresisProbabilistic neural networkArtificial neural networkbusiness.industryComputer scienceMagnetic hysteresis neural nets physics computingJiles-Atherton modelGeneral Physics and AstronomyPattern recognitionArtificial intelligencebusiness

description

In this paper a procedure for the identification of the parameters of the Jiles–Atherton (JA) model is presented. The parameters of the JA model of a material are found by using a neural network trained by a collection of hysteresis curves, whose parameters are known. After a presentation of the Jiles–Atherton model, the neural network and the training procedure are described and the method is validated by using some numerical, as well as experimental, data.

yearjournalcountryeditionlanguage
2011-04-13
10.1063/1.3569735http://hdl.handle.net/10447/80506