• D. ASHWINI
• B. N. SUHAS
• CHANDRASHEKAR C
• DARPAN M N
• PRAJWAL S

The work describes a Python-based technique for evaluating liquefaction potential. Infrastructure may suffer significant harm as a result of liquefaction, a phenomena that happens in saturated soils during earthquakes. For the purpose of creating robust buildings and reducing hazards, an accurate estimate of the potential for liquefaction is essential.The suggested approach uses a Python framework to integrate machine learning concepts, empirical correlations, and geotechnical principles. Obtaining input data, such as soil qualities, seismic parameters, and geotechnical site features, is the first step in the evaluation process. To guarantee compatibility and consistency, these data are preprocessed and standardised.Based on predetermined standards like the standard penetration test (SPT) blow count, shear wave velocity, and effective stress analysis, the liquefaction potential is assessed. Python is used to create empirical correlations and prediction models to calculate liquefaction susceptibility, liquefaction triggering potential.

Liquefaction, SPT, Python Program

"ASSESSMENT OF LIQUEFACTION POTENTIAL IN SOUTH INDIA USING AI &ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.d789-d793, August-2023, Available :http://www.jetir.org/papers/JETIR2308397.pdf

"ASSESSMENT OF LIQUEFACTION POTENTIAL IN SOUTH INDIA USING AI &ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppd789-d793, August-2023, Available at : http://www.jetir.org/papers/JETIR2308397.pdf