The use of neural networks in describing magnetisation phenomena

Abstract The application of multilayer feed-forward neural network architecture is presented for mapping of the B — H plane with a major loop and first order transition curves, and for approximation of dynamic hysteresis of soft magnetic specimens. The neural network correctly models hysteresis characteristics and constitutes a viable alternative to analytical approaches.