Prediction of Factor of Safety For Slope Stability Using Advanced Artificial Intelligence Techniques

  • Abhiram Chebrolu
  • Suvendu Kumar Sasmal
  • Rabi Narayan BeheraEmail author
  • Sarat Kumar Das
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 949)


One of the major arising challenges in geotechnical engineering is to stabilize slopes for the sake of nature, economy, and valuable lives. In recent times, there has been a tremendous amount of developments in the field of computational geomechanics leading to the development of the slope stability analysis. The study explains the application of advanced artificial intelligence methods for finding the factor of safety of the slope. Multi-gene genetic programming (MGGP) and multivariate adaptive regression splines (MARS) are the two techniques used in predicting the factor of safety (FOS) for stability analysis of slopes. The present results are compared with Sah et al. [4] and the comparison seems to be reasonably good. The study finds that MGGP is more accurate than MARS in predicting the FOS.


Slope stability Factor of safety Artificial intelligence Multi-gene genetic programming (MGGP) Multivariate adaptive regression splines (MARS) 


  1. 1.
    Friedman, J.H.: Multivariate adaptive regression splines. Ann. Stat. pp. 1–67 (1991)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Gandomi, A.H., Alavi, A.H.: Multi-stage genetic programming: a new strategy to nonlinear system modeling. Inf. Sci. 181(23), 5227–5239 (2011)CrossRefGoogle Scholar
  3. 3.
    Koza, J.R.: Genetic programming: on the programming of computers by natural selection. MIT Press, Cambridge, Mass (1992)zbMATHGoogle Scholar
  4. 4.
    Sah, N.K., Sheorey, P.R., Upadhyama, L.W.: Maximum likelihood estimation of slope stability. Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 31, 47–53 (1994)CrossRefGoogle Scholar
  5. 5.
    Searson, D.P., Leahy, D.E., Willis, M.J.: GPTIPS: an open source genetic programming toolbox from multi-gene symbolic regression. In: International Multi Conference of Engineers and Computer Scientists, vol. 1, March 17–19, Hong Kong (2010)Google Scholar
  6. 6.
    Milborrow, S.: Package ‘earth’. R Software package (2019)Google Scholar
  7. 7.
    Yang, C.X., Tham, L.G., Feng, X.T., Wang, Y.J., Lee, P.K.: Two stepped Evolutionary algorithm and its application to stability analysis. J. Comput. Civil. Engg. 18(2), 145–153 (2004)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Abhiram Chebrolu
    • 1
  • Suvendu Kumar Sasmal
    • 1
  • Rabi Narayan Behera
    • 1
    Email author
  • Sarat Kumar Das
    • 2
  1. 1.Department of Civil EngineeringNational Institute of Technology RourkelaRourkelaIndia
  2. 2.Department of Civil EngineeringIndian Institute of Technology (Indian School of Mines)DhanbadIndia

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