Determining the Natural Frequency of Cantilever Beams Using ANN and Heuristic Search

Autor:	Mehdi Nikoo, Marijana Hadzima-Nyarko, Emmanuel Karlo Nyarko, Mohammad Nikoo
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Electronic computers. Computer science QA75.5-76.95 Cybernetics Q300-390
Zdroj:	Applied Artificial Intelligence, Vol 32, Iss 3, Pp 309-334 (2018)
Druh dokumentu:	article
ISSN:	0883-9514 1087-6545 08839514
DOI:	10.1080/08839514.2018.1448003
Popis:	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.
Databáze:	Directory of Open Access Journals
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