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RETRACTED ARTICLE: Study on settlement prediction model of deep foundation pit in sand and pebble strata based on grey theory and BP neural network

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This article was retracted on 09 April 2022

An Editorial Expression of Concern to this article was published on 28 September 2021

This article has been updated

Abstract

In the process of urban underground space development, it is necessary to predict the ground settlement around the deep foundation pit to protect the surrounding environment. At present, there are few studies on the subsidence of sand and pebble strata. Furthermore, in some engineering sites with multifactor coupling effects, the theoretical calculation is large and the accuracy is low. Consequently, this study introduces the measured data analysis method and focuses on the comparative analysis of settlement prediction models based on grey theory and the back propagation (BP) neural network theory. The surface subsidence data around the deep foundation pit at the metro station in Chengdu, China (which is mainly composed of sand and pebble strata) are used to formulate a prediction and propose an optimized grey prediction model of land subsidence and a one-dimensional double-hidden-layer BP neural network subsidence prediction model. The results show that the prediction results of the two models are accurate and the final prediction results are of certain engineering reference value.

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Funding

The present work was carried out with the support of China Communications Road Construction Technology R&D Project (ZJLY-2018-44).

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Authors and Affiliations

  1. College of Construction Engineering, Jilin University, Changchun, 130026, China

    Yan Lv, Tingting Liu & Chengliang Gao

  2. MOE Key Laboratory of Geotechnical and Underground Engineering, Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China

    Jing Ma

  3. China Communication North Road & Bridge Co., Ltd., Beijing, 100020, China

    Shengda Wei

Authors
  1. Yan Lv
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  2. Tingting Liu
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  3. Jing Ma
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  4. Shengda Wei
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  5. Chengliang Gao
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Corresponding author

Correspondence to Yan Lv.

Additional information

This article is part of the Topical Collection on Big Data and Intelligent Computing Techniques in Geosciences

This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s12517-022-10082-w

Appendix

Appendix

Table 2. Subsidence data from monitoring section DB13-1 over time
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Table 3. Prediction results of the five models
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Lv, Y., Liu, T., Ma, J. et al. RETRACTED ARTICLE: Study on settlement prediction model of deep foundation pit in sand and pebble strata based on grey theory and BP neural network. Arab J Geosci 13, 1238 (2020). https://doi.org/10.1007/s12517-020-06232-7

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  • DOI: https://doi.org/10.1007/s12517-020-06232-7

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