Solving Parameter Identification of Nonlinear Problems by Artificial Bee Colony Algorithm

Table 1

A review on several examples of the parameters identification problems.

Description of the work	Studied structure	Research field	Authors
Estimation bridge’s supports conditions and material properties	Bridge	STR	Robert-Nicoud et al. [22]
Estimation of the reliability of bridge using environmental monitoring data (temperature and wind loads)	Bridge model	STR	Catbas et al. [23]
Parameter identification of Bouc-Wen model for MR fluid dampers using adaptive charged system search optimization and a hybrid algorithm	MR fluid dampers	STR	Talatahari et al. [1, 19]
Use of deflections, rotation, and strain to identify the best model of identification of geotechnical parameters combining a metaheuristic algorithm (particle swarm optimization), support machine vector, and numerical analysis to integrate nonlinear relationship between displacement and mechanical properties	Soil parameters	GEO	Zhao and Yin [24]
Identification of the water infiltration in an unsaturated soil column by using a modified particle swarm optimization algorithm	Soil parameters	GEO	Zhang et al. [25]
Identification of several geotechnical parameters on two cases: an oedometer test and an application on a natural slope	Soil parameters	GEO	Meir et al. [26]
Identification of equivalent stiffnesses of a structure that mimics soil-structure interaction parameters by inverse analysis using the particle swarm optimization algorithm	Soil-structure interaction parameters	SSI	Fontan et al. [2]
Identification of Mohr-Coulomb parameters combining displacements data, the genetic algorithm, and a Plaxis model	Mohr-Coulomb parameters	SSI	Levasseur et al. [27]
Application of the inverse analysis to modify excavation project in progress using displacement data of the buildings around the site	Excavation wall	SSI	Schmitt and Schlosser [28]

STR: structure; SSI: soil-structure interaction; GEO: geotechnical.