Application of artificial intelligence techniques to predict the performance of RC beams shear strengthened with NSM FRP rods. Formulation of design equations

Application of fuzzy logic approach in predicting the lateral confinement coefficient for RC columns wrapped with CFRP

“…Therefore, due to their capabilities of capturing the non-linear relationships existing between variables in a complex system, artificial intelligence-based models have recently been implemented for modeling of several complex systems whose behaviors are not well understood. Potential advantages and benefits of artificial intelligence-based methods have already been highlighted by many substantial studies in the relevant literature [17][18][19]. Among them, fuzzy and neuro-fuzzy techniques have gained more attention over the past decade and so.…”

Prediction of debonding strength for masonry elements retrofitted with FRP composites using neuro fuzzy and neural network approaches

“…Compressive strength of concrete containing fly ash was predicted using ANN and fuzzy logic [43]. The performance of RC beams shear strengthened with near-surface mounted FRP rods was predicted using ANN by Perera et al [44]. In this study, a multi-objective optimization problem was solved for generating a design formula of simple application to evaluate the shear strength contribution provided by a near-surface mounted system.…”

“…In the recent years novel approaches based on soft computing have been employed to civil engineering problems [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. Altun et al [30] predicted the compressive strength of steel fiber added lightweight concrete using artificial neural network (ANN).…”

Knowledge-Based Prediction of Load-Carrying Capacity of RC Flat Slab through Neural Network and FEM

“…In previous studies, ANNs have been used to estimate material behavior [36][37][38][39] as well as response of RC members [11,[40][41][42][43][44][45][46][47][48]. ANNs have achieved the advanced attention of the researcher for solving the problems, especially for estimating the ULR of composite concrete members (CCM) [49][50][51]. Also, load-carrying capacity of advance materials has been predicted using ANNs as discussed in the articles .…”