Permanent Settlement Prediction of Composite Foundation Improved by Cement-Soil Piles under Cycle Loading

Tao Ran Huo; Shun Guo Bai

doi:10.4028/www.scientific.net/AMR.482-484.1205

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 482-484Permanent Settlement Prediction of Composite...

Permanent Settlement Prediction of Composite Foundation Improved by Cement-Soil Piles under Cycle Loading

Abstract:

Through large-scale model tests on composite foundation of cement-soil piles under cyclic loading, a program was compiled based on the platform of MATLAB 7.0, considering the effects of cement mixing ratio, replacement ratio, cyclic stress ratio and number of cyclic on the permanent settlement of composite ground. A back-propagation neural network model to predict the settlement was established, and its prediction accuracy was inspected. Meanwhile, an predicting model of multivariable linear regression analysis was established .To compare the prediction accuracy of the two methods, and the result shows that the trained neural network have the better predictive and generalization.

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Periodical:

Advanced Materials Research (Volumes 482-484)

Pages:

1205-1208

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.482-484.1205

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Online since:

February 2012

Authors:

Tao Ran Huo, Shun Guo Bai

Keywords:

Composite Foundation, Cyclic Loading, Neural Network (NN), Permanent Settlement, Prediction

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References

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