Artificial Neural Network Model for Optimum Design of Tubular Columns

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In structural engineering problems, an optimum design is also a must like safety and comfort. Most of the structural optimization problems are non-linear and cannot be mathematically solved. For that reason, iterative methods like the use of a metaheuristic algorithm are generally used. The optimization process may last too long. In the present study, a prediction system based on artificial neural networks (ANNs) was developed for the cost optimization of tubular column by learning with optimum result found according to flower pollination algorithm. According to the result, the ANNs model is effective to find close solutions to optimum values obtained by the employed optimization method.


Artificial neural network, metaheuristic algorithms, flower pollination algorithm, tubular column, prediction


Cite this paper

Melda Yucel, Gebrail Bekdas, Sinan Melih Nigdeli, Selçuk Sevgen. (2018) Artificial Neural Network Model for Optimum Design of Tubular Columns. International Journal of Theoretical and Applied Mechanics, 3, 82-86


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