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Proceedings of the 2nd International Symposium on Information Processing (ISIP 2009)

Huangshan, China, August 21-23, 2009

Editors: Fei Yu, Jian Shu, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN002

ISBN: 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)

Page(s): 197-200

Estimating Model Parameters of Conditioned Soils by Using Artificial Network

Shangguan Zichang, Li Shouju, Sun Wei, and Luan Maotian

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The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function representing the difference between the experimental data and the calculated data of the mechanical model. The ill-poseness of inverse problem is discussed. The classical gradient-based optimization algorithm for parameter identification is also investigated. Neural network models are developed for estimating model parameters of conditioned soils in EBP shield. The weights of neural network are trained by using the Levenberg-Marquardt approximation which has a fast convergent ability. The parameter identification results illustrate that the proposed neural network has not only higher computing efficiency but also better identification accuracy. The results from the model are compared with simulated observations. The models are found to have good predictive ability and are expected to be very useful for estimating model parameters of conditioned soils in EBP shield.

Index Terms

parameter estimation, neural network, inverse problem, shield machine

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