Finite element model selection using Particle Swarm Optimization

  • Linda Mthembu
  • Tshilidzi Marwala
  • Michael I. Friswell
  • Sondipon Adhikari
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


This paper proposes the application of particle swarm optimization (PSO) to the problem of finite element model (FEM) selection. This problem arises when a choice of the best model for a system has to be made from set of competing models, each developed a priori from engineering judgment. PSO is a population-based stochastic search algorithm inspired by the behaviour of biological entities in nature when they are foraging for resources. Each potentially correct model is represented as a particle that exhibits both individualistic and group behaviour. Each particle moves within the model search space looking for the best solution by updating the parameters values that define it. The most important step in the particle swarm algorithm is the method of representing models which should take into account the number, location and variables of parameters to be updated. One example structural system is used to show the applicability of PSO in finding an optimal FEM. An optimal model is defined as the model that has the least number of updated parameters and has the smallest parameter variable variation from the mean material properties. Two different objective functions are used to compare performance of the PSO algorithm.


Particle Swarm Optimization Finite Element Model Akaike Information Criterion Particle Swarm Optimization Algorithm Inertia Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Linda Mthembu
    • 1
  • Tshilidzi Marwala
    • 2
  • Michael I. Friswell
    • 3
  • Sondipon Adhikari
    • 3
  1. 1.Department of Electronic and Computer Engineering, Faculty of Engineering and Built EnvironmentUniversity of JohannesburgDoornfonteinSouth Africa
  2. 2.Faculty of Engineering and Built EnvironmentUniversity of JohannesburgDoornfonteinSouth Africa
  3. 3.School of EngineeringSwansea UniversitySwanseaUK

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