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Structural Engineering and Mechanics Volume 56, Number 5, December10 2015 , pages 787-796 DOI: https://doi.org/10.12989/sem.2015.56.5.787 |
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Neuro-fuzzy and artificial neural networks modeling of uniform temperature effects of symmetric parabolic haunched beams |
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S. Bahadir Yuksel and Alpaslan Yarar
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| Abstract | ||
| When the temperature of a structure varies, there is a tendency to produce changes in the shape of the structure. The resulting actions may be of considerable importance in the analysis of the structures having non-prismatic members. The computation of design forces for the non-prismatic beams having symmetrical parabolic haunches (NBSPH) is fairly difficult because of the parabolic change of the cross section. Due to their non-prismatic geometrical configuration, their assessment, particularly the computation of fixed-end horizontal forces and fixed-end moments becomes a complex problem. In this study, the efficiency of the Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) in predicting the design forces and the design moments of the NBSPH due to temperature changes was investigated. Previously obtained finite element analyses results in the literature were used to train and test the ANN and ANFIS models. The performances of the different models were evaluated by comparing the corresponding values of mean squared errors (MSE) and decisive coefficients (R2). In addition to this, the comparison of ANN and ANFIS with traditional methods was made by setting up Linear-regression (LR) model. | ||
| Key Words | ||
| non-prismatic member; finite element analysis; parabolic haunch; artificial neural networks, adaptive neuro fuzzy inference systems | ||
| Address | ||
| S. Bahadir Yüksel and Alpaslan Yarar: Department of Civil Engineering, Selcuk University, 42075 Konya, Turkey | ||