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A single-valued neutrosophic Gaussian process regression approach for stability prediction of open-pit mine slopes

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The accurate prediction of the stability of open-pit mine slopes is usually one of the difficult problems faced by mining engineers and researchers, which is caused by the indeterminacy and uncertainty contained in the influence factors of stability of open-pit mine slopes. The single-valued neutrosophic number (SVNN) is very suitable for representing the information of truth, falsity, and indeterminacy in inconsistent and indeterminate situations. This paper proposes a method combining SVNN with Gaussian process regression (SVNN-GPR) to evaluate the open-pit mine slopes stability in uncertain environment. At first, the proposed method expresses the uncertain influence factors/indices (dip of potential failure plane, cohesion, friction angle, etc.) and the stability state of open-pit mine slopes as SVNNs. Then, the SVNN-GPR is established to obtain the latent complicated relationship between SVNN influence factors and slope stability. Finally, we use the score values of the SVNN output of the proposed method to predict the stability of each slope. To test the performance of the proposed method, we collected 286 slope cases from Zhejiang Province, China. The practical application results reflect that the SVNN-GPR method based on the exponential covariance function and isotropic distance measure has best training and testing results, and the training accuracy reaches 98.0% and the testing accuracy reaches 96.5%. This shows the proposed SVNN-GPR method provides a new effective way for predicting open-pit mine slopes stability in inconsistent and indeterminate situations.

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Authors and Affiliations

  1. State Key Laboratory for GeoMechanics and Deep Underground Engineering, China University of Mining and Technology-Beijing, Beijing, 100083, People’s Republic of China

    Jibo Qin & Xiaoming Sun

  2. School of Mechanics and Civil Engineering, China University of Mining and Technology-Beijing, Beijing, 100083, People’s Republic of China

    Jibo Qin & Xiaoming Sun

  3. Institute of Rock Mechanics, Ningbo University, Ningbo, Zhejiang, 315211, People’s Republic of China

    Jun Ye, Rui Yong & Shigui Du

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  1. Jibo Qin
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Correspondence to Shigui Du.

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CRediT author statement

Jibo Qin: Data curation, Methodology, Software, Writing-Original draft. Jun Ye: Validation, Writing-Review & Editing. Xiaoming Sun: Resources, Formal analysis. Rui Yong: Investigation, Writing-Review. Shigui Du: Conceptualization, Supervision.

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Qin, J., Ye, J., Sun, X. et al. A single-valued neutrosophic Gaussian process regression approach for stability prediction of open-pit mine slopes. Appl Intell 53, 13206–13223 (2023). https://doi.org/10.1007/s10489-022-04089-9

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