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Research Article
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Back Analysis Method of Foundation Pit Soil Mechanical Parameters Based on GA-BP Neural Network
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Jiang Ping
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ABSTRACT
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In order to ensure the foundation pit construction safety,
displacement monitoring was carried on the foundation pit soil. At the same
time, according to the measured displacement, the displacement parameters inversion
algorithm was taken to calculate the foundation pit soil mechanical parameters,
then calculate the stability of foundation pit soil. According to the basic
calculation method of genetic algorithm optimizing neural network, in this paper,
use uniform design method to design the samples of the foundation pit soil displacement
and mechanical parameters. The finite element analysis was used to calculate
soil displacement with different parameters. The GA-BP neural network was trained
to describe the sophisticated nonlinear relationship between displacement and
mechanical parameters of the foundation pit soil. Finally, the actual displacement
was input into the trained GA-BP neural network to obtain the soil mechanical
parameters. As an example, the soil cohesion, friction angle, elastic modulus
and Poisson ratio of Changchun West Railway Station foundation pit were back-analysis
by the above method. The calculation displacement obtained by finite element
analysis with inversion results and compared with measured data. The comparison
result shows that GA-BP neural network has high precision in excavation soil
parameters inversion which can meet the needs of engineering.
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