This article presents a new modified cuckoo search algorithm with dynamic discovery
probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological …

This paper presents a useful approach to optimally design magnetorheological (MR)
dampers used in structural buildings. To fulfill this aim, damper parameters are regarded as …

Particle swarm optimization (PSO) technique has achieved a considerable success in
solving nonlinear, nondifferentiable, multi-modal optimization problems. Currently, PSO is …

In this article, the charged system search (CSS) optimization method is improved to identify
the parameters of a non-linear hysteretic Bouc-Wen differential model. The CSS is suitable …

In the current research, the imperialist competitive algorithm is dramatically enhanced and a
new optimization method dubbed as Enriched Imperialist Competitive Algorithm (EICA) is …

In this article, a new two-stage hybrid optimization method based on the Particle Swarm
Optimization and the Big Bang-Big Crunch algorithm (BB-BC) is introduced for identification …

To overcome the shortcomings of the Bouc–Wen model, such as too many parameters,
complex identification process, and long time consuming, the sensitivity of parameters was …

To solve the problems of low identification accuracy and complex identification methods in
the Bouc-Wen model of the magnetorheological (MR) damper, a new parameter …

In this research, novel genetic algorithm (nGA) is proposed for Bouc-Wen modle parameters
esstimation for magnetorheological (MR) fluid dampers. The optimization efficiency is …

In this paper, a new hybrid algorithm based on charged system search (CSS) and colliding
bodies optimization (CBO) is proposed to identify the parameters of a highly nonlinear semi …