English

Finite Element Model Updating Using Fish School Search Optimization Method

Computational Engineering, Finance, and Science 2013-08-13 v1 Neural and Evolutionary Computing

Abstract

A recent nature inspired optimization algorithm, Fish School Search (FSS) is applied to the finite element model (FEM) updating problem. This method is tested on a GARTEUR SM-AG19 aeroplane structure. The results of this algorithm are compared with two other metaheuristic algorithms; Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). It is observed that on average, the FSS and PSO algorithms give more accurate results than the GA. A minor modification to the FSS is proposed. This modification improves the performance of FSS on the FEM updating problem which has a constrained search space.

Keywords

Cite

@article{arxiv.1308.2307,
  title  = {Finite Element Model Updating Using Fish School Search Optimization Method},
  author = {I. Boulkabeit and L. Mthembu and T. Marwala and F. De Lima Neto},
  journal= {arXiv preprint arXiv:1308.2307},
  year   = {2013}
}

Comments

To appear in the 1st BRICS Countries & 11th CBIC Brazilian Congress on Computational Intelligence

R2 v1 2026-06-22T01:07:23.968Z