## 7 Conclusions  
The work describes the applicability of ANN modelling to simple and complex RC members under different loading conditions i.e.: (i) RC beams in simply supported condition without transverse steel or stirrups (BWOS) and RC beams in simply supported condition with transverse steel or stirrups (BWS), (ii) RC columns in cantilever supported conditions (CWA), (iii) RC T-beams in simply supported conditions without transverse steel or stirrups (TBWOS) and RC T-beams in simply supported condition with transverse steel or stirrups (TBWS) and (iv) RC flat slabs in simply supported condition under a punching load (SCS). The optimized ANN model among the other ANN models is selected based on the corresponding R value. The R value of the BWOS-4 (i.e., \(d\), \(M_{g}\)/\(bd^{2}\), \(f\), \(c\), \(a_{w}\)/\(d\)) is 97%, for BWS-7 (i.e., \(d\), \(b\)/\(d\), \(M\)/\(df_{c}\)\(bd^{2}\), \(f_{w}\), \(d_{w}\)/\(d\)) it is 98%, for CWA-3 (i.e., \(b\)/\(d\), \(N\)/\(bd\), \(M\)/\(df_{c}\)\(bd^{2}\), \(\rho_{w}\), \(f_{w}\), \(a_{w}\)/\(d\)) it is 97%, for TBWOS:02 (i.e., \(b_{w}\), \(d\), \(f_{c}\), \(M\)/\(df_{c}\)\(bd^{2}\), \(h_{p}\), \(b_{r}\), \(a_{w}\)/\(d\),) it is 97%, for TBWS: 03 (i.e., \(b_{w}\)/\(d\), \(\rho_{p}\)/\(\rho_{b}\)/\(\rho_{b}\), \(f_{c}\)/\(f_{w}\), \(b\)/\(h_{r}\), \(a_{w}\)/\(d\)) it is 98% and for SCS:4 (\(c\)/\(d\), \(a_{w}\)/\(d\), \(\rho_{p}\)/\(f_{c}\)/\(f_{w}\)) it is 97% for optimized models among the other ANN models. A comparative study showed the predictions of non-conventional models, i.e.: ANN models, are closer to the provided experimental values related to the other physical models i.e., CFP and CDCs.  
Figure 34: Normal Distribution for SCS.  
Figure 35: Ratio Distribution for SCS.  
This result is similar to the results of other researchers [55; 56; 57; 58; 59] working on the different databases. Unlike the conventional methodology, soft computing techniques like ANN models have the capabilities to predict the response of RC members with simple or complex geometry under different loading conditions. Once the ANNs are trained on the provided database, they can provide an accurate prediction without concerning material behavior and the mechanics underlying the RC structural response at ULS. The comparative study conducted between the predicted values for the RC members concerning the ultimate response shows the results from the ANN are close to CFP and EC-2 and more accurate as compared to those obtained from the ACI Code.  
The Conceptualization, A.A. and D.M.C., methodology, N.D.L. and software, A.A. and N.D.L.; validation, A.A. and D.M.C. data curation, D.M.C., writing--original draft preparation, A.A. and N.D.L. Authorship must be limited to those who have contributed substantially to the work reported. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This research received no external funding. Not applicable. Not applicable. Not applicable. Data Availability Statement: The details of all database will be published after completion of the on-going research by using MDPI data journal. Not applicable. Not applicable. The authors declare no conflict of interest.