This study investigates an adaptive-weighted instanced-based learning, for the prediction of the ultimate punching shear capacity\n(UPSC) of fiber-reinforced polymer- (FRP-) reinforced slabs.Theconcept of the newmethod is to employ theDifferential Evolution\nto construct an adaptive instance-based regressionmodel.The performance of the proposedmodel is compared to thoseofArtificial\nNeural Network (ANN) and traditional formula-based methods. A dataset which contains the testing results of FRP-reinforced\nconcrete slabs has been collected to establish and verify new approach. This study shows that the investigated instance-based\nregression model is capable of delivering the prediction result which is far more accurate than traditional formulas and very\ncompetitivewith the black-box approach ofANN. Furthermore, the proposed adaptive-weighted instanced-based learning provides\na means for quantifying the relevancy of each factor used for the prediction of UPSC of FRP-reinforced slabs.
Loading....