Determining the Natural Frequency of Cantilever Beams using ANN and Heuristic Search (CROSBI ID 249205)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Nikoo, Mehdi ; Hadzima-Nyarko, Marijana ; Nyarko, Emmanuel Karlo ; Nikoo, Mohammad
engleski
Determining the Natural Frequency of Cantilever Beams using ANN and Heuristic Search
An Artificial Neural Network 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, 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.
Cantilever Beam ; First Mode Frequency ; Artificial Neural Network, Imperialist Competitive Algorithm ; Genetic Algorithm ; Particle Swarm Optimization Algorithm
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
32 (3)
2018.
309-334
objavljeno
0883-9514
1087-6545
10.1080/08839514.2018.1448003
Povezanost rada
Građevinarstvo, Računarstvo