  Genetic programming has been widely used in the engineering field. Compared
with the conventional genetic programming and artificial neural network,
geometric semantic genetic programming (GSGP) is superior in astringency and
computing efficiency. In this paper, GSGP is adopted for the classification and
regression analysis of a sample dataset. Furthermore, a model for slope
stability analysis is established on the basis of geometric semantics.
According to the results of the study based on GSGP, the method can analyze
slope stability objectively and is highly precise in predicting slope stability
and safety factors. Hence, the predicted results can be used as a reference for
slope safety design.
