Method of Deformation Probability Prediction Considering the Influence of Uncertainty Factors

doi:10.11947/j.AGCS.2017.20160531

Abstract

Abstract: A probabilistic prediction method of deformation is proposed based on the MCMC algorithm and the Bayesian Prediction Theory.This method describes the uncertainty of deformation prediction using probability distributions and implement the recursive process of prediction by probability rules. The settlement data from the Nanjing-Hangzhou high-speed roadbed is used to quantitatively analyze the forecast values, reliability intervals and so on, and then the results are compared with those obtained by the least squares estimation and the immune algorithm, and it has shown that the proposed method is effective and feasible.

Key words: prediction uncertainty, measurement error, parameter uncertainty, Gibbs sampling, probability predication

CLC Number:

P258

WEI Guanjun, DANG Yamin, ZHANG Chuanyin, YANG Weifang. Method of Deformation Probability Prediction Considering the Influence of Uncertainty Factors[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(4): 526-532.

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