An evolutionary algorithm-based artificial neural network (ANN) to identify structural damage
and nonlinear hysteresis parameters simultaneously is presented. To avoid the 'dimensional …

Hysteretic models are used to describe the nonlinear memory-based relationship between
the input and output of some physical systems. A long short-term memory neural network …

In this paper, a new type of multilayer feedforward neural network has been proposed based
on inspiration from the Preisach model, which has been called the Preisach neural network …

In this paper, a new kind of activation function using a particular combination of stop and
play operators is proposed and used in a feedforward neural network to improve its learning …

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems.
The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous …

This study attempts to demystify a powerful neural network approach for modelling non-
linear hysteretic systems and in turn to streamline its architecture to achieve better …

Hysteresis is a ubiquitous phenomenon describing the special nonlinear memory-based
relation between the input and the output in many physical systems. Identifying the hysteretic …

The experimental dynamical response of three types of nonlinear hysteretic systems is
identified employing phenomenological models togheter with the Differential Evolutionary …

Nonlinear hysteretic systems are common in many engineering problems. The maximum
response estimation of a nonlinear hysteretic system under stochastic excitations is an …

Cyclic behavior of materials is complex and difficult to model. A combination of hardening
rules in classical plasticity is one possibility for modeling this complex material behavior …