![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
ABSTRACT
An artificial neural network (ANN) is used to model the frequency of the first mode, using the beam length, the moment of inertia, and the load applied on the beam as input parameters on a database of 100 samples. Three different heuristic optimization methods are used to train the ANN: genetic algorithm (GA), particle swarm optimization algorithm and imperialist competitive algorithm. The suitability of these algorithms in training ANN is determined based on accuracy and runtime performance. Results show that, in determining the natural frequency of cantilever beams, the ANN model trained using GA outperforms the other models in terms of accuracy.
Notes
1. ICA was downloaded from: http://www.mathworks.com/matlabcentral/fileexchange/22046-imperialist-competitive-algorithm–ica-. PSO was downloaded from: http://www.particleswarm.info/SPSO2011_matlab.zip.
Both were accessed on January 7, 2015.