Shear Strength of Reinforced Concrete Frame Column by Neural Network Model

Abstract:

The artificial neural networks (BP-ANN) established by the back-propagation algorithm and early stopping technique. By inputting the properties of geometries and material, BP-ANN model can predict the ultimate shear strength of reinforced concrete frame column. The BP-ANN model based on feed-forward neural network is built, trained and tested using the available test data of 82 RC frame column collected from the technical literature. And the test results are compared and analyzed with predictions based on the current the code of China and ACI code. It shows that the reinforced concrete frame column shear strengths obtained by the simplified model based on BP-ANN are in good agreement with test results, and they are closer to the experimental values than the results designed by models in codes. The BP-ANN model can be used in the shear strength prediction and design for reinforced concrete frame column.

• Periodical: Advanced Materials Research (Volumes 1065-1069)
• Pages: 1234-1239
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1065-1069.1234
• Online since: December 2014
• Authors: Xi Liu*, Hui Wei, Tao Wu, Bo Quan Liu, Yu Zhang
• Keywords: BP-ANN Model, Frame Column, Reinforced Concrete, Shear Capacity

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