Prediction of stratum deformation during the excavation of a foundation pit in composite formation based on the artificial bee colony–back-propagation model

Abstract

A method for predicting deformation during the excavation of a foundation pit in composite formation is proposed. The artificial bee colony algorithm (ABC) is introduced to optimize the back-propagation (BP) neural network with the input variables filtered. This method is applied to predict the deformation of a foundation pit project. The prediction results are verified by comparing the results with those of other neural network models. The results indicate that the depth of excavation, speed of excavation, friction angle in the soil, gravity, elastic modulus and number of internal support layers are the main factors affecting the deformation of the soil layer around the foundation pit. The ABC algorithm is capable of searching for better solutions of initial weights and thresholds. The ABC-BP model with a 6-12-2 network structure has high prediction accuracy and the best generalization ability.