Static properties model of magnetically controlled shape memory alloy based on neural networks

Based on the experimental data obtained from static properties test of magnetically controlled shape memory alloy, using the function of approximation of BP neural networks, the forecasting modelling was established. The experimental data and the forecasting data agreed well and the error was only 0.04%, which indicates that the modelling had good accuracy. The neural networks modelling can avoid the problem to calculate the modelling parameters based on the material physical properties and solve the material inherent coupling problem between magnetic field, the force fields and temperature field. It provided a new method to research the properties of magnetically controlled shape memory alloy.