@article { author = {Ilkhani, Mohammad Hosein and Moradi, Ehsan and Lavasani, Mohammad}, title = {Calculation of Torsion Capacity of the Reinforced Concrete Beams Using Artificial Neural Network}, journal = {Journal of Soft Computing in Civil Engineering}, volume = {1}, number = {2}, pages = {8-18}, year = {2017}, publisher = {Pouyan Press}, issn = {2588-2872}, eissn = {2588-2872}, doi = {10.22115/scce.2017.48685}, abstract = {This paper presents a model for calculation of torsion capacity of the reinforced concrete beams using the artificial neural network. Considering the complex reaction of reinforced concrete beams under torsion moments, torsion strength of these beams is depended on different parameters; therefore using the artificial neural network is a proper method for estimating the torsion capacity of the beams. In the presented model the beam's dimensions, concrete compressive strength and longitudinal and traverse bars properties are the input data, and torsion capacity of the reinforced concrete beam is the output of the model. Also considering the neural network results, a sensitivity analysis is performed on the network layers weight, and the effect of different parameters is evaluated on the torsion strength of the reinforced concrete beams. According to the sensitivity analysis, properties of traverse steel have the most effect on torsion capacity of the beams.}, keywords = {Neural Network,Torsion,RC Beam}, url = {https://www.jsoftcivil.com/article_48685.html}, eprint = {https://www.jsoftcivil.com/article_48685_7c8e3840821038bd09162762d3bb6f3d.pdf} }