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The global sensitivity analysis of slope stability based on the least angle regression

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Listed:
  • Zhaoxia Xu

    (Chongqing University)

  • Xiaoping Zhou

    (Chongqing University
    Chongqing University
    Chongqing University)

  • Qihu Qian

    (Chongqing University)

Abstract

The least angle sensitivity (LARS) algorithm is used to realize the global sensitivity analysis of slope stability, while simultaneously considering the effects of several geotechnical parameters on slope stability. In addition, the Sobol sequence is applied in the sample simulation to generate the geotechnical parameters, thereby increasing the accuracy of the results. Two cases are considered to investigate the effects of the geotechnical parameters on slope stability, and the accuracy and efficiency of the LARS algorithm are examined. The importance measure indexes obtained using the LARS algorithm are in good agreement with those obtained using the Monte Carlo (MC) method. To determine the importance measure indexes, the performance functions of the slope stability analysis are required to be run N times when using the LARS algorithm, which is $$1/(n \cdot N + 1)$$ 1 / ( n · N + 1 ) the required number for the MC method, where n and N represent the number of random variables and sample size, respectively. In this scenario, the computational efficiency is considerably increased.

Suggested Citation

  • Zhaoxia Xu & Xiaoping Zhou & Qihu Qian, 2021. "The global sensitivity analysis of slope stability based on the least angle regression," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2361-2379, February.
    • Handle: RePEc:spr:nathaz:v:105:y:2021:i:3:d:10.1007_s11069-020-04403-z
    DOI: 10.1007/s11069-020-04403-z
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    References listed on IDEAS

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    1. Nahid Vatanpour & Mohammad Ghafoori & Hossein Talouki, 2014. "Probabilistic and sensitivity analyses of effective geotechnical parameters on rock slope stability: a case study of an urban area in northeast Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(3), pages 1659-1678, April.
    2. T. Siddque & S. P. Pradhan, 2018. "Stability and sensitivity analysis of Himalayan road cut debris slopes: an investigation along NH-58, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 577-600, September.
    3. Xiao, Sinan & Lu, Zhenzhou & Wang, Pan, 2018. "Multivariate global sensitivity analysis for dynamic models based on wavelet analysis," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 20-30.
    4. J. Shaji, 2014. "Coastal sensitivity assessment for Thiruvananthapuram, west coast of India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(3), pages 1369-1392, September.
    5. Alfons, Andreas & Croux, Christophe & Gelper, Sarah, 2016. "Robust groupwise least angle regression," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 421-435.
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