Tall Building Subsidence Data Regression Analysis Methods and the Final Settlement Value Prediction

Zhong Yin Xu; Shan Jun Liu; Li Xin Wu

doi:10.4028/www.scientific.net/AMM.226-228.1228

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 226-228Tall Building Subsidence Data Regression Analysis...

Tall Building Subsidence Data Regression Analysis Methods and the Final Settlement Value Prediction

Abstract:

In order to provide reference data for the safe construction and validation of the design method is correct, the subsidence monitoring for tall buildings (high-rise structures) which are being in the construction or completed. In this paper according to the actual settlement monitoring data, on basis of considering the construction stage, the settlement data were segmented regression analysis. The results show that in stage of load (in construction) uniform increasing, the settlement and load a linear regression analysis results are better than the results of settlement with time linear regression analysis, While in the building after the completion, the settlement with time were the logarithm function regression analysis, hyperbolic regression analysis and power function regression analysis. The regression analysis results show that hyperbola regression analysis method is of minimum variance and the regression analysis effect is best, the final settlement value was predicted and providing reference basis for construction and design.

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Periodical:

Applied Mechanics and Materials (Volumes 226-228)

Pages:

1228-1231

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.226-228.1228

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Online since:

November 2012

Authors:

Zhong Yin Xu, Shan Jun Liu, Li Xin Wu

Keywords:

Prediction, Regression Analysis, Subsidence Monitoring, Variance

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