Symbolic regression-based prediction of coefficient of permeability for granular soils

Key Points

• Coefficient of permeability can be effectively predicted using symbolic regression techniques, enhancing predictive modeling capabilities.
• Findings suggest that using symbolic regression can lead to more accurate predictions in soil behavior, moving beyond traditional methods.
• Analysis reveals significant correlations between soil properties and permeability metrics, providing robust insights into granular soil dynamics.
• Assessment through innovative modeling techniques may enable improved engineering practices for soil stability and water retention.