ISSN 2096-4498

   CN 44-1745/U

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Study of Large Deformation Prediction of Soft Rock Tunnel  Based on Progressive Composite Combined Prediction Model

  • ZHAO Shumin
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  • (Shaanxi Railway Institute, Weinan 714000, Shaanxi, China)

Received date: 2017-07-10

  Revised date: 2017-12-20

  Online published: 2018-07-28

Abstract

In order to realize the judgment of the development trend of large deformation of tunnel, optimize the site construction, and avoid construction safety risk, the LSSVM and optimized GM (1, 1) models are adopted to predict the deformation of tunnel. And then the quadratic sum of error is taken as an index, and the prediction results of the two models are combined. Finally, the BP neural network is used to modify the prediction error so as to realize comprehensive prediction. The case test results show that the optimization effect on support vector machine by least squares method is superior to that by grey model; and the error modification model can further effectively improve the prediction accuracy, which make the predicted and measured values closer. Meanwhile, the prediction results show that the deformation of later 4 cycles are still with continuous deformation trend, which indicates that effective measures should be adopted to avoid accidents. The abovementioned prediction model has better prediction accuracy and applicability, which has a certain significance for the study of large deformation of tunnel.

Cite this article

ZHAO Shumin . Study of Large Deformation Prediction of Soft Rock Tunnel  Based on Progressive Composite Combined Prediction Model[J]. Tunnel Construction, 2018 , 38(7) : 1131 -1137 . DOI: 10.3973/j.issn.2096-4498.2018.07.008

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