Genetic Programming For Lateral Displacement Prediction Of Deep Foundation Pit Bracing Structures

Infrastructure construction projects are developing rapidly in China, a large number of construction projects are closely related to deep foundation pit. Foundation pit engineering is complex and unpredictable, so the research for lateral displacement prediction of foundation pit bracing structures can provide the reference for the foundation safety and stability, promote the optimization of design and construction for foundation pit, and it can be conducive to the prevention and reduction of the foundation pit accident, reducing casualties and property losses.This thesis was analyzed the present domestic and foreign intelligent algorithm of the deformation of the bracing structure of foundation pit, compared and summarized their advantages and limitations when applied in foundation pit engineering. Then it was introduced genetic programming model and the analysis of the model principle and characteristics. Base on the theory, genetic programming model was used to forecast the deformation of foundation pit. The deformation mechanism and types foundation pit was introduced and it focused on the displacement influence factors such as depth of excavation, dimension, strut stiffness, wall thickness and length and excavation stage. The key work was the establishment of genetic programming model and the parameters set, including the fitness function, the probability of selection, crossover and mutation probability. Meanwhile, the engineering data was used to train and test the model, screening out the final result expression, and then the results were compared with the results of the neural network model to check the accuracy and reliability. In the end, Wuhan metro deep foundation pit excavation data was used to validate the final result, the results proved that the model for displacement prediction of the bracing structure of foundation pit was reliable and practical.This study involves fields of excavation engineering and computer programming, combining different areas in a new angle. It provides a new idea for the lateral deformation prediction of deep foundation promoting practical engineering application of genetic programming. The thesis also provides important practical significance for excavation safety and economic value, which is useful for excavation deformation and providing useful reference for similar projects.