Application of GM(1,1) Model in Surface Settlement Prediction in the Maglev Protected Area

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Song-Tao Hu ◽  
Guo-Qiang Wang ◽  
Feng Ye ◽  
Guo-Feng Zeng ◽  
Xiao-Tong Gao
Keyword(s):  
Protected Area ◽  
Surface Settlement ◽  
Settlement Prediction ◽  
Surface Settlement Prediction

Settlement Prediction of Buildings Based on BP Neural Network

2014 ◽  
Vol 602-605 ◽  
pp. 3232-3234
Author(s):  
Jian Cheng Li
Keyword(s):  
Neural Network ◽  
Seismic Performance ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Existing Buildings ◽  
Large Area ◽  
Settlement Prediction ◽  
Prediction Result ◽  
Study Results

At present, the traditional neural network model have been used in settlement prediction of buildings area, but there are some limitations. In this paper, BP neural network is applied in the settlement prediction of buildings and the prediction result is compared with the measured values. The results show that: the use of BP neural network to predict the settlement of existing buildings is feasible. The study results can provide a reference for the anti-seismic performance census of existing large area buildings.

Surface settlement prediction for EPB shield tunneling in sandy ground

2017 ◽  
Vol 21 (7) ◽  
pp. 2908-2918 ◽  
Author(s):  
Yong Fang ◽  
Chuan He ◽  
Ali Nazem ◽  
Zhigang Yao ◽  
Jacob Grasmick
Keyword(s):  
Surface Settlement ◽  
Shield Tunneling ◽  
Settlement Prediction ◽  
Sandy Ground ◽  
Surface Settlement Prediction ◽  
Epb Shield

Research on surface settlement prediction based on the combination prediction model of S-shaped growth curves

2018 ◽  
Vol 21 (4) ◽  
pp. 236-241 ◽  
Author(s):  
Ying Su ◽  
Xiaoqin Wang ◽  
Yuanyuan Fu ◽  
Xianjun Zheng ◽  
Gaoshuai You
Keyword(s):  
Prediction Model ◽  
Growth Curves ◽  
Surface Settlement ◽  
Settlement Prediction ◽  
Surface Settlement Prediction
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