227 / 2018-07-23 17:02:03
Slope stability analysis for circular mode failure: a gradient boosting machine approach
Slope stability; circular failure; Gradient boosting machine (GBM); Cross-validation; predictive modeling
Draft Accepted
健 周 / 中南大学
恩铭 李 / 中南大学
珊 杨 / 中南大学
明政 王 / Laurentian University
秀志 史 / 中南大学
曙 姚 / 中金岭南
Hani S Mitri / McGill University
Slope stability analysis is one of the most crucial problems in civil and geotechnical engineering. This paper presents a gradient boosting machine (GBM) method to analyze the slope stability. The GBM- based model is developed by free R programs, trained and tested with the parameters obtained from the detailed investigation of 134 different actual slope cases available in the literature. The stability of the circular slope is taken as a function of unit weight (γ), cohesion (c), angle of internal friction (φ), slope angle (β), slope height (H) and pore water pressure coefficient (ru). A tenfold cross-validation procedure is implemented to determine the optimal parameter values during the GBM modeling and an external testing set is employed to validate the prediction performance of models. Classification accuracy rate and Cohen’s Kappa coefficient have been employed for measuring the performance of the proposed model. The analysis of accuracy together with kappa for the dataset demonstrate that the GBM model has high credibility as it achieves a comparable classification accuracy rate and Cohen’s kappa values of 87.10% and 0.7427 for the prediction of slope stability, respectively.
Important Date
  • Conference Date

    Oct 22

    2018

    to

    Oct 24

    2018

  • May 31 2018

    Abstract Submission Deadline

  • Jul 05 2018

    Draft paper submission deadline

  • Aug 10 2018

    Draft Paper Acceptance Notification

  • Oct 24 2018

    Registration deadline

Sponsored By
University of Science and Technology Beijing
McGill University
China University of Mining and Technology (Beijing)
Henan Polytechnic University
Notheastern University
Chongqing University
China University of Mining and Technology
Laurentian University
University of Wollongong
Liaoning Technical University
Xi’an University of Science and Technology
North China University of Technology
Jiangxi University of Science and Technology
Heilongjiang University of Science and Technology
Supported By
中国职业安全健康协会
中国安全生产科学研究院
煤炭信息研究院
中安安全工程研究院
International Journal of Mining Science and Technology
Safety Science
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