Prediction method of surface settlement of rectangular pipe jacking tunnel based on improved PSO-BP neural network

Abstract

To provide theoretical support for the safety control of rectangular pipe jacking tunnels crossing an existing expressway, a method for predicting the surface settlement of a rectangular pipe jacking tunnel is proposed in this study. Therefore, based on the high approximation of the BP neural network to any function under the multiparameter input, the PSO-BP mixed prediction model of the ground subsidence of the ultrashallow buried large section rectangular pipe jacking tunnel is established by taking into account the adaptive mutation method, adopting the improved particle swarm optimization (IPSO) algorithm with adaptive inertia weight and mutation particles in the later stage to determine the optimal hyperparameters of the prediction model. Through the case study of an ultrashallow large cross-section rectangular pipe jacking tunnel, this algorithm is compared with the traditional algorithm and combined with field monitoring data for analysis and prediction. The prediction results show that compared with the traditional BP neural network prediction model, AWPSO-BP model and PWPSO-BP model, the improved PSO-BP mixed prediction model shows a more stable prediction effect when the change in surface subsidence is gentle and the concavity and convexity are large. The predicted subsidence value is close to the actual value, and the accuracy and robustness of the prediction are significantly improved.

Financial big data management and intelligence based on computer intelligent algorithm

“…The famous “error backpropagation” neural network was proposed in 1985, which is a forward-forward neural network with one or more layers 28 . It not only has the characteristics of parallel processing, distributed storage, fault tolerance, etc., but also has the characteristics of self-learning, self-organization, and adaptability 29 , 30 . The BP algorithm does not need to make strict assumptions about the input variables, but just introduces noise into the input variables, with no need to know the relationship between variables and factors, as shown in Fig.…”

Ground Settlement Law, Jacking Force Prediction, and Control Countermeasures for Large-Section Rectangular Pipe Jacking of National Highway Underpass

“…By analyzing the data of the earth pressure, pore water pressure, soil displacement, and surface settlement of a rectangular pipe jacking in Nanjing, Sun et al [12] studied the law of surface settlement caused by rectangular pipe jacking construction and found that the surface settlement is mainly caused by the back soil effect. Hu et al [13] proposed a method for predicting the surface settlement of a rectangular pipe jacking tunnel crossing an existing expressway. The improved particle swarm optimization (IPSO)-BP hybrid prediction model can predict the surface settlement law during the construction process in the ultra-shallow buried large-section rectangular pipe jacking tunnel project, and the results are more accurate, which can provide new ideas for settlement pre-control of similar projects.…”