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February 20, 2024Elektronika ir ElektrotechnikaOpen Access

Surface Deformation Prediction Model of High and Steep Open-Pit Slope Based on APSO and TWSVM

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Authors

SDSunwen DuRSRuiting SongQQQing Qu

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Overview

Comparative analysis demonstrates improved surface deformation prediction in open-pit slopes, highlighting enhanced stability for mine monitoring.

Key Points

  • A surface deformation prediction model integrating adaptive subgroup optimisation and twin support vector machine achieves superior forecasting precision.
  • The model achieves a 1.27 % mean absolute error and 3.02 % RMSE, cutting prediction time by 62.5 % compared to genetic algorithm optimisation.
  • Analysis of open-pit slope monitoring data demonstrates that introducing position and velocity factors into twin support vector machine improves mine safety.

Cite This Study

Du et al. (2024) studied this question.

synapsesocial.com/papers/68e786f4b6db6435876f95ebhttps://doi.org/10.5755/j02.eie.36115
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Practical Prediction Model for Surface Deformation of Open-Pit Mine Slopes Based on Artificial Intelligence2024 · 1 citations
  2. 2Prediction of Deformation in Expansive Soil Landslides Utilizing AMPSO-SVR2024 · 1 citations
  3. 3An improved CS-SVM model for slope deformation forecasting under a BIM-based monitoring system2025
  4. 4Deformation analysis and prediction of an instability area in an open pit slope in Canada using multi-source field data and machine learning algorithms2026
  5. 5High slope deformation prediction based on residual modified ARIMA-PSO-GRNN models2024