
The main aim of the study was to perform selection procedure in order to find the optimal predictors for the shear strength of fibre reinforced polymers (FRP) used as internal reinforcement for reinforced concrete (RC) beams. The procedure was performed by adaptive neuro fuzzy inference system (ANFIS) and all available parameters are included. The ANFIS model could be used as simplification of the shear strength analysis of the FRP-RC beams. MATLAB software was used for the ANFIS application for the shear strength prediction of the FRP-RC beams. The results from the searching procedure indicated that ?beam width? and ?effective depth? form the optimal combination of two input attributes or two predictors for the shear strength prediction of the FRP-RC beams. This selected two predictors could be used effectively to estimate the strength of the FRP-RC beams.
predictors, anfis, Architecture, shear strength, TA1-2040, reinforced concrete, Engineering (General). Civil engineering (General), NA1-9428, frp
predictors, anfis, Architecture, shear strength, TA1-2040, reinforced concrete, Engineering (General). Civil engineering (General), NA1-9428, frp
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
