J06 - Identification of Bouc–Wen hysteretic systems using particle swarm optimization

Title: Identification of Bouc–Wen hysteretic systems using particle swarm optimization
Author(s): Charalampakis AE, Dimou CK
Journal: Computers and Structures
Publisher: Elsevier
Volume: 88
Issue: -
Pages: 1197–1205
Date: 2010
DOI: 10.1016/j.compstruc.2010.06.009
Language: English

[abstract]

In this paper, two variants of the particle swarm optimization (PSO) algorithm are employed for the identification of Bouc–Wen hysteretic systems. The first variant is simple while the other is enhanced, as it implements additional operators. The algorithms are utilized for the identification of a Bouc–Wen hysteretic system that represents a full scale bolted–welded steel connection. The purpose of this work is to assess their comparative performance against other evolutionary algorithms in a highly non-linear identification problem on various levels of computational budget. The enhanced PSO algorithm outperforms its competitors in terms of both accuracy and robustness.

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[cite :  RIS BibTex, or manually as : Charalampakis AE, Dimou CK. Identification of Bouc–Wen hysteretic systems using particle swarm optimization. Computers and Structures, 88 (2010): 1197–1205, doi:10.1016/j.compstruc.2010.06.009.] 

[cited by (data extracted on Apr 5, 2018) : 45 in Google Scholar, 29 in Microsoft Academic, 30 in Scopus (excluding self-citations of all authors)]