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A Novel ANN Technique for Fast Prediction of Structural Behavior
(6th International Conference WE BUILD THE FUTURE 2022 International Construction Management Conference November 17-18, 2022, Belgrade, Serbia, 2022)
In recent decades, different concepts of machine learning (ML) have found applications in solving many engineering problems. Less time consumption in performing analyses, better optimization of the quality-price ratio and ...
Estimation of ultimate strength of slender ccfst columns using artificial neural networks
(16th Congress of Association of Structural Engineers of Serbia, 2022)
This paper proposes the use of artificial neural network (ANN) algorithms to estimate the ultimate compressive strength of slender circular concrete-filled steel tubular (CCFST) columns. A dataset of 1051 samples was applied ...
Prediction of Ultimate Compressive Strength of CCFT Columns Using Machine Learning Algorithms
(8th International Conference Science and Practice, Kolasin, Montenegro, 2022)
The composite concrete-filled steel tube columns are structural members with numerous advantages over the traditional reinforced concrete or the pure steel members. The behavior of these columns is highly nonlinear. This ...
Axial Strength Prediction of Square CFST Columns Based on The ANN Model
(First Serbian International Conference on Applied Artificial Intelligence, Kragujevac, Serbia, 2022)
Due to numerous advantages, concrete-filled steel tubular (CFST) columns have an increasingly important role in the civil engineering industry. Because of the expensive experimental testing of these members, it is beneficial ...