Fundamental Theroy and Experimental Research

A combination method for predicting settlement based on new or old degree of data and adjustment of value interval of prediction

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  • Institute of Geotechnical Engineering, Hunan University, Changsha, Hunan 410082, China

Received date: 2015-05-26

  Online published: 2018-06-05

Supported by

This work was supported by the National Natural Science Foundation of China (51378198) and the Research Fund for the Doctoral Program of Higher Education of China (20130161110017).

Abstract

The prediction for post-construction settlement of building foundation or roadbed is an important basis for its safety assessment and the determination of maintenance strategy. Therefore, firstly, a methodology of combination prediction is introduced in this paper. By considering the effect of new or old degree of the measured settlement data on the prediction of post-construction settlement, an analytical model is developed by introducing a fresh-degree function, which can reflect the effect of the new or old degree of measured settlement data on prediction. Secondly, using parallel-modification, a method of the adjustment of value interval for combination prediction is proposed through analyzing the variations of the possible combination prediction, to improve the precision of the prediction. And then, on the basis, an improved model for combination prediction of post-construction settlement is established, which can simultaneously describe the effect of new or old degree of the measured data and the effect of adjustment of value interval for combination prediction on settlement prediction. Finally, the proposed method is used to analyze the practical engineering examples, which demonstrates that the method is feasible and reasonable.

Cite this article

CAO Wen-gui, YIN Peng, HE Min, LIU Tao . A combination method for predicting settlement based on new or old degree of data and adjustment of value interval of prediction[J]. Rock and Soil Mechanics, 2017 , 38(2) : 534 -540 . DOI: 10.16285/j.rsm.2017.02.029

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