This work aims to provide a broad overview of computational techniques belonging to the
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …

This paper will introduce the use of the approximate Bayesian computation (ABC) algorithm
for model selection and parameter estimation in structural dynamics. ABC is a likelihood-free …

This paper presents the use of the multiobjective particle swarm optimization (PSO)
technique for the identification of Jiles-Atherton model parameters. This approach …

The basic physical processes can be rigorously treated using the quantum mechanics. This
is done at atomic level and is far from the aim of this chapter. Other approaches at …

A magnetic hysteresis model is developed based on the vector generalization of Jiles-
Atherton (JA) model combined with a simplified multiscale approach to take into account the …

The analysis and optimization of devices with soft magnetic cores, such as inductive sensors
and electric machines, rely on a simple and precise modelling of their nonlinear anhysteretic …

Abstract The parameters of Bouc–Wen hysteresis model are identified using a Modified
Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to …

The paper presents results of validation of the anhysteretic magnetization model for a soft
amorphous alloy with significant perpendicular anisotropy. The validation was carried out for …

The objective of this study is to identify the dynamic material properties of human passive
muscle tissues for the strain rates relevant to automobile crashes. A novel methodology …

摘要基于JA 磁滞模型模拟铁磁材料磁滞特性的关键是模型参数的精确快速辨识.
该文针对现有JA 磁滞模型参数提取方法存在的收敛速度慢, 求解精度低的问题 …