DocumentCode
2099785
Title
Application of BFGS-BP in Tunnel Deformation Monitoring Data Processing
Author
Zegen, Wang ; Yuyun, Gao ; Guangqiang, Hu
Author_Institution
Sch. of Civil Eng. & Archit., Southwest Pet. Univ., Chengdu, China
fYear
2011
fDate
17-18 Sept. 2011
Firstpage
411
Lastpage
414
Abstract
In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-BFGS method for unconstrained extreme problem is introduced into BP neural network algorithm, and a BFGS-BP neural network model is developed, which is applied well in tunnel deformation monitoring data processing and forecasting with uncertainty and nonlinearity. With the example of the observation data of vault crown settlement of some tunnel construction process, the test of training and forecast experiments of BFGS - BP were developed. The result shows that BFGS-BP model has higher calculation precision and convergence rate than the traditional one.
Keywords
backpropagation; condition monitoring; deformation; geotechnical engineering; neural nets; optimisation; structural engineering computing; tunnels; BFGS-BP model; convergence rate; nonlinear optimization method BFGS method; traditional BP neural network algorithm; tunnel deformation monitoring data processing; Data models; Data processing; Deformable models; Monitoring; Prediction algorithms; Predictive models; Training; BFGS algorithm; BP neural network; data processing; deformation monitoring;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4577-1561-7
Type
conf
DOI
10.1109/ICICIS.2011.107
Filename
6063284
Link To Document