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


Nikoo, Mehdi; Hadzima-Nyarko, Marijana; Nyarko, Emmanuel Karlo; Nikoo, Mohammad
Determining the Natural Frequency of Cantilever Beams using ANN and Heuristic Search // Applied artificial intelligence, 32 (2018), 3; 309-334 doi:10.1080/08839514.2018.1448003 (međunarodna recenzija, članak, znanstveni)


Naslov
Determining the Natural Frequency of Cantilever Beams using ANN and Heuristic Search

Autori
Nikoo, Mehdi ; Hadzima-Nyarko, Marijana ; Nyarko, Emmanuel Karlo ; Nikoo, Mohammad

Izvornik
Applied artificial intelligence (0883-9514) 32 (2018), 3; 309-334

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Cantilever Beam ; First Mode Frequency ; Artificial Neural Network, Imperialist Competitive Algorithm ; Genetic Algorithm ; Particle Swarm Optimization Algorithm

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo, Računarstvo



POVEZANOST RADA


Ustanove
Građevinski i arhitektonski fakultet Osijek,
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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