Modified imperialist competitive algorithm-based neural network to determine shear strength of concrete beams reinforced with FRP

Abstract

Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest; however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.

Keywords

concrete shear strength / fiber reinforced polymer (FRP) / artificial neural networks (ANNs) / Levenberg-Marquardt algorithm / imperialist competitive algorithm (ICA)

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