Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Structural Engineering and Mechanics Volume 73, Number 4, February25 2020 , pages 463-479 DOI: https://doi.org/10.12989/sem.2020.73.4.463 |
|
|
|
Practical optimization of power transmission towers using the RBF-based ABC algorithm |
||
Faezeh Taheri, Mohammad Reza Ghasemi and Babak Dizangian
|
||
| Abstract | ||
| This paper is aimed to address a simultaneous optimization of the size, shape, and topology of steel lattice towers through a combination of the radial basis function (RBF) neural networks and the artificial bee colony (ABC) metaheuristic algorithm to reduce the computational time because mere metaheuristic optimization algorithms require much time for calculations. To verify the results, use has been made of the CIGRÉ Tower and a 132 kV transmission towers as numerical examples both based on the design requirements of the ASCE10-97, and the size, shape, and topology have been optimized (in both cases) once by the RBF neural network and once by the MSTOWER analyzer. A comparison of the results shows that the neural network-based method has been able to yield acceptable results through much less computational time. | ||
| Key Words | ||
| optimization; power transmission towers; steel lattice towers; RBF neural network; artificial bee colony (ABC) algorithm | ||
| Address | ||
| Faezeh Taheri, Mohammad Reza Ghasemi: Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran Babak Dizangian: Department of Civil Engineering, Velayat University, Iranshahr, Iran | ||