Predicting the settlement of geosynthetic-reinforced soil foundations using evolutionary artificial intelligence technique

In order to ensure safe and sustainable design of geosynthetic-reinforced soil foundation (GRSF), settlement prediction is a challenging task for practising civil/geotechnical engineers. this paper, new hybrid technique predicting the GRSF has been proposed based on combination evolutionary algorithm, that is, grey-wolf optimisation (GWO) artificial neural network (ANN), abbreviated as ANN-GWO model. For purpose, reliable pertinent data were generated through numerical simulations conducted validated large-scale 3-D finite element The predictive power model was assessed using various well-established statistical indices, also against several independent scientific studies reported in literature. Furthermore, sensitivity analysis examine robustness reliability results obtained have indicated developed can estimate maximum under service loads intelligent way, thus, be deployed tool preliminary GRSF. Finally, translated into functional relationship which executed without need any expensive computer-based program.