Abstract:
This project presents the development of a new empirical prediction model to evaluate
swell pressure of expansive soils (Ps-ES). An extensive database comprising 168 Ps
records was established after a comprehensive literature search. The performance of
developed model was tested using mean absolute error (MAE), root squared error (RSE),
root mean square error (RMSE), correlation coefficient (R), regression coefficient (R2).
The results in the increasing order of the contribution of each input parameter is in the order
of OMC (28.27) > PI (27.59) > CF (14.59) > MDD (12.59) > SP (10.40) > silt (6.55).
The MEP model outperformed the other AI models found in literature for the prediction
of swell pressure in terms of closeness of training, validation and testing data set with the
ideal fit slope. The findings of this study can help researchers and designers to evaluate the
swell characteristics of the expansive soils in pre-planning and pre-design phases of a
construction project and for validation of the laboratory and field test results.
