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

2011

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.

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