ACM Transactions on Mathematical Software (TOMS)
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
SIAM Journal on Optimization
Journal of Global Optimization
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Model updating using neural networks
Model updating using neural networks
Structural damage detection using neural network with learning rate improvement
Computers and Structures
Algal bloom prediction with particle swarm optimization algorithm
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
Short Communication: Parameter sensitivity study of the Nelder-Mead Simplex Method
Advances in Engineering Software
A poly-hybrid PSO optimization method with intelligent parameter adjustment
Advances in Engineering Software
On the application of bees algorithm to the problem of crack detection of beam-type structures
Computers and Structures
Advances in Engineering Software
Mathematical and Computer Modelling: An International Journal
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
Finite Elements in Analysis and Design
Special Genetic Identification Algorithm with smoothing in the frequency domain
Advances in Engineering Software
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This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO"b). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results.