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Finite Element Model Updating Using Fish School Search Optimization Method

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.

preprint2013arXivOpen access
I. BoulkabeitL. MthembuT. MarwalaF. De Lima Neto
Computational Engineering, Finance, and ScienceNeural and Evolutionary Computing
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Open access4 authors2 topics
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
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I. BoulkabeitL. MthembuT. MarwalaF. De Lima Neto

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