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A new, fast, and accurate algorithm for predicting soil slope stability based on sparrow search algorithm-back propagation

Author

Listed:
  • Binbin Zheng

    (Shandong Technology and Business University
    Shandong Technology and Business University)

  • Jiahe Wang

    (Shandong Technology and Business University)

  • Shuhu Feng

    (Shandong Technology and Business University
    Shandong Technology and Business University)

  • Han Yang

    (Chongqing University)

  • Wensong Wang

    (Chengdu University of Technology)

  • Tingting Feng

    (Shandong Technology and Business University)

  • Tianyu Hu

    (Chongqing Jiaotong University)

Abstract

Slope stability prediction is one of the most essential and critical tasks in mining and geotechnical projects. A fast and precise slope stability prediction is crucial for safe operations and cost-effective slope maintenance. In this work, a back propagation (BP) neural network based on a sparrow search algorithm (SSA) is developed to predict the slope safety coefficients by using five input features, including unit weight (γ), cohesion (c), friction angle (φ), slope angle (α), and slope height (H). The proposed model is trained and simulated using 55 data samples. The regression coefficient of the proposed SSA-BP neural network is 0.9405, with a mean relative error (MAE) of 0.1684. Compared with fusion algorithms, such as Ridge Regression (RR), Decision Tree (DT), Random forest (RF), Support Vector Regression (SVR), and Light Gradient Boosting Machine (lightGBM), the proposed method yields more accurate and robust prediction results. Furthermore, a multivariate function relationship between the slope safety coefficient and the five variables is constructed based on the relationship between five independent input variables and the variation of the safety coefficient. The proposed method introduces a novel approach for calculating the slope safety coefficient.

Suggested Citation

  • Binbin Zheng & Jiahe Wang & Shuhu Feng & Han Yang & Wensong Wang & Tingting Feng & Tianyu Hu, 2024. "A new, fast, and accurate algorithm for predicting soil slope stability based on sparrow search algorithm-back propagation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(1), pages 297-319, January.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:1:d:10.1007_s11069-023-06210-8
    DOI: 10.1007/s11069-023-06210-8
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