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Geomechanics and Engineering
  Volume 13, Number 3, September 2017 , pages 447-458

Sensitivity analysis of the influencing factors of slope stability based on LS-SVM
Juncai Xu, Qingwen Ren and Zhenzhong Shen

    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.
Key Words
    slope stability; sensitivity analysis; orthogonal design; least squares support vector machine; gray correlation
(1) Juncai Xu, Qingwen Ren, Zhenzhong Shen:
College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China;
(2) Juncai Xu:
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.

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