Predicting the Shear Strength of Fiber Reinforced Concrete Corbels Via Support Vector Machines
Abstract
Precast corbels are commonly preferred structural members in industrial
buildings. In this study, a novel application of support vector machines (SVM)
is employed for the prediction of ultimate shear strength of fiber reinforced
corbels, for the first time in literature. SVM models are developed and analyzed
using a database of available test results in literature. Predictions of the
selected model are compared against the test results and those of available
model proposed by Fattuhi (1994). Proposed model has the capability to predict
the shear strength of both steel fiber reinforced concrete (SFRC) and glass
fiber reinforced concrete (GFRC) corbels. Additionally, a parametric study with
a wide range of variables is carried out to test the effect of each parameter
on the shear strength. The results confirm the high prediction capacity of
proposed model.
Keywords
References
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