International Journal of Optimization in Civil Engineering
عنوان نشریه
IJOCE
Engineering & Technology
http://ijoce.iust.ac.ir
18
agent2
2228-7558
doi
en
jalali
1402
11
1
gregorian
2024
2
1
14
2
online
1
fulltext
en
PREDICTION OF NATURAL FREQUENCIES FOR TRUSS STRUCTURES WITH UNCERTAINTY USING THE SUPPORT VECTOR MACHINE AND MONTE CARLO SIMULATION
Applications
Applications
پژوهشي
Research
<span style="font-size:11.5pt"><span style="text-autospace:none"><span new="" roman="" style="font-family:" times="">In this study, the support vector machine and Monte Carlo simulation are applied to predict natural frequencies of truss structures with uncertainties. Material and geometrical properties (e.g., elasticity modulus and cross-section area) of the structure are assumed to be random variables. Thus, the effects of multiple random variables on natural frequencies are investigated. Monte Carlo simulation is used for probabilistic eigenvalue analysis of the structure. In order to reduce the computational cost of Monte Carlo simulation, a support vector machine model is trained to predict the required natural frequencies of the structure computed in the simulations. The provided examples demonstrate the computational efficiency and accuracy of the proposed method compared to the direct Monte Carlo simulation in the computation of the natural frequencies for trusses with random parameters.</span></span></span><br>
Machine learning, support vector machine, truss, random eigenvalue problem, uncertainty quantification, monte carlo simulation.
211
228
http://ijoce.iust.ac.ir/browse.php?a_code=A-10-66-402&slc_lang=en&sid=1
Pooya
Zakian
p-zakian@araku.ac.ir
`180031947532846002185`

180031947532846002185
Yes
Department of Civil Engineering, Faculty of Engineering, Arak University, Arak, Iran
Pegah
Zakian
`180031947532846002186`

180031947532846002186
No
Department of Electrical Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran