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Retaining walls are one of the most common geotechnical structures. Horizontal displacement at the top of the retaining wall is an important parameter in design of retaining structures because of serviceability of the wall and adjacent structures. In this research, the Gene Expression Programming (GEP) is used for developing a model to predict this design parameter of retaining wall. The input parameters of the model consist of eective period of adjacent structure, horizontal and rocking stiness of the foundation of adjacent structure, density, Young's modulus, and friction angle of granular soil as well as the thickness and height of retaining wall. The output of the model is maximum lateral displacement of retaining wall. A database including 240 cases, created from 3D nite element modeling of a soil-retaining wall with an adjacent steel structure modeled as surcharge, is employed to develop the model. Comparison of the GEP-based model predictions with the simulated data indicates a very good performance and ability of the developed models in predicting maximum lateral displacement of retaining walls. Sensitivity and parametric analyses are conducted to verify the results. It is shown that soil density is the most in uential parameter in the maximum lateral displacement of retaining wall.

A genetic-based model to predict maximum lateral displacement of retaining wall in granular soil