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 …

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, 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 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 …

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 …

In this paper, a new opposition based charged system search (CSS) is proposed to be used
as a parameter identification of highly nonlinear semi-active magneto-rheological damper …

The nonlinear dynamic hysteretic models used in nonlinear dynamic analysis contain
generally lots of model parameters which need to be identified accurately and effectively …

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

The main objective of this paper is to investigate efficiency and correctness of different real-
coded genetic algorithms and identification criteria in nonlinear system identification within …

In most cases, the standard optimization algorithms are capable of identifying the required
number of parameters for a specific design problem; however, this process is difficult and …