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

Authors

  • Sunwen Du College of Mining Engineering, Taiyuan University of Technology, Taiyuan, P. R. China
  • Ruiting Song College of Mining Engineering, Taiyuan University of Technology, Taiyuan, P. R. China
  • Qing Qu Faculty of Mechanical Engineering, Opole University of Technology, Opole, Poland
  • Zhiying Zhao Shanxi Province Coal-Based Resources Green and High-Efficiency Development Engineering Center, Taiyuan, P. R. China
  • Hailing Sun Shanxi Province Coal-Based Resources Green and High-Efficiency Development Engineering Center, Taiyuan, P. R. China
  • Yanwei Chen Shanxi Province Coal-Based Resources Green and High-Efficiency Development Engineering Center, Taiyuan, P. R. China

DOI:

https://doi.org/10.5755/j02.eie.36115

Keywords:

High and steep slope, Slope surface deformation prediction, Twin support vector machine, Adaptive subgroup optimisation

Abstract

At present, due to the complex and changeable geological conditions, the precise deformation prediction technology of high and steep slope could not achieve an accurate prediction. In particular, the single forecasting model has some problems such as poor stability, low precision, and data fluctuation. In practice, excavating the complex nonlinear relationship between open-pit slope surface deformation monitoring data and various influencing factors and improving the accuracy of the deformation prediction of high and steep slopes is the key to safe open-pit mine production. It proposed to introduce the position factor and the velocity factor into a twin support vector machine (TWSVM). The adaptive subgroup optimisation (APSO) algorithm is selected for parameter optimisation. Through the comparative analysis of TWSVM, genetic algorithm-TWSVM (GA-TWSVM), and the proposed APSO⁃TWSVM, the experimental data show that the mean absolute error (MAE) values of the three models are 13.29 %,8.17 %, and 1.27 %, the RMSE - 47.83 %,6.52 %, and 3.02 %, respectively; the prediction time for APSO⁃TWSVM is improved by 62.5 % compared to GA-TWSVM.

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Published

2024-02-20

How to Cite

Du, S., Song, R., Qu, Q., Zhao, Z., Sun, H., & Chen, Y. (2024). Surface Deformation Prediction Model of High and Steep Open-Pit Slope Based on APSO and TWSVM. Elektronika Ir Elektrotechnika, 30(1), 77-83. https://doi.org/10.5755/j02.eie.36115

Issue

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY