Geomechanics and Engineering

  • 제13권3호
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  • Pages.447-458
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  • 2017
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  • 2005-307X(pISSN)
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  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Sensitivity analysis of the influencing factors of slope stability based on LS-SVM

  • Xu, Juncai (College of Water Conservancy and Hydropower Engineering, Hohai University) ;
  • Ren, Qingwen (College of Water Conservancy and Hydropower Engineering, Hohai University) ;
  • Shen, Zhenzhong (College of Water Conservancy and Hydropower Engineering, Hohai University)
  • 투고 : 2016.02.13
  • 심사 : 2017.03.27
  • 발행 : 2017.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

This study proposes a sensitivity analysis method for slope stability based on the least squares support vector machine (LS-SVM) to examine the influencing factors of slope stability. The method uses LS-SVM as an algorithm for machine learning. An appropriate training dataset is established according to the slope characteristics, and a testing dataset is designed orthogonally. Results of the testing data in the experiment design are calculated after training using the LS-SVM model. The sensitivity of the slope stability of each factor is examined via gray correlation analysis. The results are consistent with those of the traditional Bishop analysis and can be used as a reference for optimizing slope design.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China

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