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 :
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