**5. Conclusion**

494 Fuzzy Inference System – Theory and Applications

ANN ANFIS ACI440 El-Sayed Eq. Tureyen Eq. ANN

0 100 200 300 400 500

*V (Target) kN*

Fig. 19. Comparison experimental and predicted values for testing data set

0

100

200

300

*Vu (Predicted) (kN)*

400

500

Fig. 20. Comparison experimental and predicted values for testing data set

Table 8. Comparison summary of correlation R

Type Correlation R

Tureyen and Frosch's Eq. 0.37 0.69

ANN 0.995 0.993 ANFIS 0.99 0.97 El-Sayed's Eq. 0..32 0.63 ACI 440 0.51 0.78

Training Testing

Two civil engineering applications are preformed using back-propagation neural network (BPNN)and adaptive neuro fuzzy inference system (ANFIS). The models were developed by predicting the shear strength of ferrocement members and the shear strength of concrete beams reinforced with fiber reinforced polymer (FRP) bars using BPNN and ANFIS based on the results of experimental lab work conducted by different authors. From the results of this study, the following conclusions can be stated:

