Prediction of Shear Strength of Soft Soil using Python

Authors

  • Adwaith A. Dept. of Civil Engineering, Bishop Jerome Institute, Kollam, Kerala Author
  • Arjun A. Dept. of Civil Engineering, Bishop Jerome Institute, Kollam, Kerala Author
  • Bijoy Fernandez Dept. of Civil Engineering, Bishop Jerome Institute, Kollam, Kerala Author
  • Josna J. Dept. of Civil Engineering, Bishop Jerome Institute, Kollam, Kerala Author
  • Shobana Dept. of Civil Engineering, Bishop Jerome Institute, Kollam, Kerala Author

DOI:

https://doi.org/10.21467/proceedings.7.8.4

Abstract

Shear strength is a crucial parameter in determining the stability of soil structures. Accurate prediction of this parameter can significantly reduce the time and cost involved in conventional testing methods. This study presents a machine learning-based model developed in Python to predict the shear strength of soft soils using geotechnical properties such as moisture content, liquid limit, plastic limit, and specific gravity. Data was collected from different districts and processed to train the model. The results demonstrate the potential of Python-based algorithms in forecasting shear strength with a reasonable degree of accuracy

References

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Published

2025-11-27

Issue

Vol. 7 No. 8 (2025): Proceedings of the National Conference on Emerging Trends and Innovation (NCETI-25)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

[1]
Adwaith A., Arjun A., B. Fernandez, Josna J., and Shobana, “Prediction of Shear Strength of Soft Soil using Python”, AIJR Proc., vol. 7, no. 8, pp. 25–33, Nov. 2025, doi: 10.21467/proceedings.7.8.4.