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Research on slope reliability analysis using multi-kernel relevance vector machine and advanced first-order second-moment method

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Abstract

To increase the efficiency and accuracy in slope stability analysis, a reliability analysis method based on machine learning and the advanced first-order second-moment (AFOSM) method was proposed, and the partial derivative of the machine-learning algorithm was derived. First, a multi-kernel was introduced to establish the multi-kernel relevance vector machine (MKRVM). Then, the kernel parameters of the MKRVM were optimized by the harmony search (HS) method to use the high-precision MKRVM method instead of the traditional methods for determining the factor of safety. It was necessary to obtain the partial derivative of the performance function, which was explicitly expressed by the trained MKRVM in this paper. Finally, the AFOSM was adopted to calculate the reliability index of the slope, as the AFOSM was more reliable because the design point was located at the failure surface. With two samples, from a single-layer slope and a multilayer slope, the calculation results show that the MKRVM–AFOSM is easy to use, highly computationally efficient, and reliable.

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Code availability

The RVM toolbox from the corresponding paper, Tipping [27].

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Acknowledgements

The authors are grateful to Mike Tipping for the RVM toolbox, and Zhao Hongbo and Pijush Samui for the data.

Funding

This research was funded by the Key Projects of Natural Science Basic Research Program of Shaanxi Province Grant number [2018JZ5010], the Water Science Plan Project of Shaanxi Province Grant number [2018SLKJ-5] and Joint Funds of Natural Science Fundamental Research Program of Shaanxi Province of China and the Hanjiang-to-Weihe River Valley Water Diversion Project Grant number [2019JLM-55].

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Authors and Affiliations

  1. State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an, 710048, China

    Chun hui Ma, Jie Yang, Lin Cheng & Li Ran

Authors
  1. Chun hui Ma
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  2. Jie Yang
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  3. Lin Cheng
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  4. Li Ran
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Contributions

Conceptualization: [CM]; methodology: [CM]; software: [CM]; data curation: [CM]; writing—original draft preparation: [CM]; supervision: [JY]; funding acquisition: [JY]; writing—review and editing: [LC]; validation: [LR]. All the authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Jie Yang.

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Conflict of interest

The authors declare that they have no conflict of interest.

Availability of data and material

Some data and models used during the study are available from the corresponding paper (Zhao [23]; Zhao et al. [24]; Samui et al. [15]).

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Ma, C.h., Yang, J., Cheng, L. et al. Research on slope reliability analysis using multi-kernel relevance vector machine and advanced first-order second-moment method. Engineering with Computers 38, 3057–3068 (2022). https://doi.org/10.1007/s00366-021-01331-9

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  • DOI: https://doi.org/10.1007/s00366-021-01331-9

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