Genetic algorithms and neural networks generalizing the Jiles - Atherton model of static hysteresis for dynamic loops

IEEE Transactions on Magnetics

Volumn 38, Issue 2 I, 2002, Pages 873-876

  Salvini, Alessandro ^a   Fulginei, Francesco Riganti ^a  

^a ROMA TRE UNIVERSITY   (Italy)

Author keywords

Genetic algorithms; Hysteresis; Neural network applications

Indexed keywords

FINITE ELEMENT METHOD; GENETIC ALGORITHMS; MAGNETIC FIELDS; MATHEMATICAL MODELS; NEURAL NETWORKS;

DYNAMIC LOOPS; STATIC HYSTERESIS;

MAGNETIC HYSTERESIS;

EID: 0036493847     PISSN: 00189464     EISSN: None     Source Type: Journal    
DOI: 10.1109/20.996225     Document Type: Article

References (12)

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5. Prediction of dynamic hysteresis under highly distorted exciting fields by neural networks and actual frequency transplantation
6. Modeling the effects of eddy current losses on frequency dependent hysteresis in electrically conducting media
7. Automatic and accurate evaluation of the parameters of a magnetic hysteresis model
8. General properties of power losses in soft ferromagnetic materials
9. A wide bandwidth, dynamic hysteresis model for magnetization in soft ferrites
10. A self consistent generalized model for calculation of minor loop excursion in the theory of hysteresis