Modeling strength enhancement of FRP confined concrete cylinders using soft computing

This study presents the application of soft computing techniques namely as genetic programming (GP) and stepwise regression (SR), neuro-fuzzy (NF) and neural networks (NN) for modeling of strength enhancement of FRP (fiber–reinforced polymer) confined concrete cylinders. The proposed soft computing models are based on experimental results collected from literature. The accuracy of the proposed soft computing models are quite satisfactory as compared to experimental results. Moreover the results of proposed soft computing formulations are compared with 10 models existing in the literature proposed by various researchers so far and are found to be by far more accurate.