Volume 39 Issue 2
Apr.  2025
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Wang Sai, Zhang Yahui, Wang Yuncheng, Fan Haobo. Prediction of road settlement caused by LGWO top pipe tunnel construction[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2025, 39(2): 192-199. doi: 10.20265/j.cnki.issn.1007-2993.2024-0187
Citation: Wang Sai, Zhang Yahui, Wang Yuncheng, Fan Haobo. Prediction of road settlement caused by LGWO top pipe tunnel construction[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2025, 39(2): 192-199. doi: 10.20265/j.cnki.issn.1007-2993.2024-0187
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Prediction of road settlement caused by LGWO top pipe tunnel construction

doi: 10.20265/j.cnki.issn.1007-2993.2024-0187
  • 1.

    Hebei Human Defense Engineering Design & Research Institute Co., Ltd., Shijiazhuang 050000, Hebei, China

  • 2.

    Department of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China

  • 3.

    Hebei Urban & Rural Construction School, Shijiazhuang 050031, Hebei, China

  • 4.

    China Railway Design Group Co., Ltd., Geographic Information Research Institute, Tianjin 300308, China

  • Received Date: 2024-05-06
  • Accepted Date: 2024-08-29
  • Rev Recd Date: 2024-06-19
    • Available Online: 2025-04-07
  • Publish Date: 2025-04-08
    Abstract
  • To accurately predict the deformation and settlement caused by a large cross-section pipe tunnel passing through the existing highway, a settlement prediction model based on the adaptive Grey Wolf optimization algorithm was proposed in conjunction with the actual project. Logistic mapping was introduced to generate the initial value, and the convergence factor A in the Grey Wolf algorithm is decomposed into decision factor and attenuation factor to improve the lack of ability of the convergence factor in global and local search. Through the Cangzhou Jiuhe Road Passage human security project for example verification, and with the traditional Grey Wolf algorithm, particle swarm algorithm to compare the prediction accuracy, the analysis results show that the accuracy of Grey Wolf algorithm prediction optimized by Logistic mapping is higher. The accuracy increased by 6.9% compared with the Grey Wolf algorithm without optimization and increased by 2.3% compared with the particle swarm algorithm. The new model has a high degree of practicality and accuracy.

     

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