In this study, a database including 159 experimental beam results gathered from the available literature was used for the development of an artificial neural network (ANN) model in an effort to predict the bond strength between GFRP bars and concrete. Two ANN models using BFGS quasi-Newton backpropagation and conjugate gradient backpropagation with Polak-Ribiére algorithms were constructed and evaluated in terms of bond strength prediction accuracy. |