Finite element model updating using fish school search optimization method

Ilyes Boulkabeit, Linda Mthembu, Tshilidzi Marwala, Fernando Buarque De Lima Neto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013
PublisherIEEE Computer Society
Pages447-452
Number of pages6
ISBN (Print)9781479931941
DOIs
Publication statusPublished - 2013
Event1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013 - Recife, Brazil
Duration: 8 Sept 201311 Sept 2013

Publication series

NameProceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013

Conference

Conference1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013
Country/TerritoryBrazil
CityRecife
Period8/09/1311/09/13

Keywords

  • Finite Element Model (FEM)
  • Fish School Search (FSS)
  • Genetic Algorithm (GA)
  • Particle Swarm Optimization (PSO)

ASJC Scopus subject areas

  • Artificial Intelligence

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