Research on Prediction of Deformation Value of the Foundation Pit Based On Bayesian and LSTM Neural Network Models
In order to improve the accuracy and reliability of pit deformation prediction,a composite model was pro-posed based on Bayesian method(Bayes)and long short-term memory(LSTM)neural network in this paper.Com-bined with the site monitoring data of Wenyi West Road renovation project,the prediction error of surface settlement and horizontal displacement data above the large span pit was compared by Bayes-LSTM model with other prediction models.The results show that the prediction accuracy has been improved by Bayes-LSTM model by 1.0 and 1.26 re-spectively compared with the LSTM model and the SVM(support vector machine)model,which is proved to have high prediction accuracy and generalization ability in the prediction of surface settlement.The study provides decision support for the safety management of large-span foundation pit construction.
foundation pit settlementBayesian networklong short-term memory(LSTM)neural networkpredic-tive model
万方数据
维普
