2013/08/10 by I. Boulkabeit, L. Mthembu, Boulkabeit, I. +5
Computer Science · #Computational Engineering #FOS: Computer and information sciences #Finance #Neural and Evolutionary Computing (cs.NE) #and Science (cs.CE) #cs.CE #cs.NE
paper · pdf · doi:10.48550/arxiv.1308.2307
To appear in the 1st BRICS Countries & 11th CBIC Brazilian Congress on Computational Intelligence
arxiv created 2013/08/10 · arxiv updated 2013/08/13
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.