Study On Monitoring Data Analysis And Deformation Prediction Of Deep Foundation Pit

With the rapid development of city construction, the use of ur ban space increasingly nervous, while the development of underground space eas es the contradiction well. One kind of type is deep foundation pit engineering w hich is very complicated and important as the part of bearing the weight of the u pper structure, and its stable or not related to the safety of the upper structure, even had an impact on the deformation of the surrounding buildings, so its defor mation prediction receiving more and more attention of scholars.The pit deformation is influenced by so many factors that it is difficult to use the mechanical model or unified experience formula to compute the deformation. In order to guide the foundation pit excavation, avoiding safety accident in the process of constructing, protecting the stability of the surrounding buildings effectively, this paper will be based on the former research, use the observation data in the process of deep foundation pit of Beijing excavation of monitoring stations, with the early data to predict the late deformation of the foundation pit.This paper introduces the gray system method and artificial neural network method and detailed analysis the basic theory of these two methods are used in prediction. In some extent the two methods can do deformation forecast in certain conditions, while there are shortcomings. The gray system method looking for the sorting of law through the original data, it is suitable for prediction of the deformation of growing exponentially short-term time series. In the case of monitoring data sequence is very short, the prediction results of artificial neural network method are relatively large error.According to this kind of situation, this paper will be discussed a new method which combination with the advantage of the grey system method can be accurately predict short-term deformation and BP neural network model. Based on one foundation pit engineering monitoring data, do some analysis of foundation pit deformation forecast method. This paper based on the Matlab software, respectively for the gray system GM (1,1) model and artificial neural network model to forecast analysis contrast, and then combine with the two methods, using this optimization model to do analysis. The deep foundation pit deformation forecast results of the optimization model show that they are have higher precision sex and accuracy, using this model can forecast the trend of foundation pit deformation well, achieve good prediction effect, explain the suggested method has high reliability and applicability.