Forecasting the bearing capacity of the mixed soil using artificial neural network

The bearing capacity of soil changes owing to the mechanical properties of the soil and it influences the structural stability. In most of the geotechnical engineering projects, there are several soil mechanic experiments, that need interpretation before application. The mechanical properties of soil interaction make the prediction of soil bearing capacity complex. However, the enhancement of construction project safety needs the interpretation of soil experiments and design results for proper application in a geotechnical engineering project. In this study, artificial neural network is proposed for the evaluation of the mixed soil characteristics to forecast the safe bearing capacity of soil due to the mechanical properties of the soil interaction phenomenon. The results for prediction of the safe bearing capacity reveal that the R-2 and RMSE for all mechanical properties effects on safe bearing capacity are 0.98 and 0.02, these values can provide a suitable accuracy for the prediction of the safe bearing capacity of the mixed soil. The higher inaccuracy is obtained when only the influence of single mechanical property on the mixed soil is considered in the prediction of the safe bearing capacity. This study supports the enhancement of geotechnical engineering design quality through the prediction of safe bearing capacity from characterized mechanical properties of the soil.