Estimating the permeability coefficient of soil using CART and GMDH approaches

Abstract Permeability coefficient of soil (k) is one the most important parameters in groundwater studies. This study, two robust explicit data-driven methods, Including classification and regression trees (CART) group method data handling (GMDH) were developed using characteristics soil, i.e., clay content (CC), water (?), liquid limit (LL), plastic (PL), specific density (?), void ratio (e) to generate predictive equations for prediction k. When compared CART; mean absolute error (MAE) = 0.0051, root square (RMSE) 0.0088, scatter index (SI) 64.00%, correlation (R) 0.7841, agreement (IA) 0.8830; GMDH equation produced lowest values; MAE 0.0044, RMSE 0.0072, SI 52.17%, R 0.8493, Ia 0.9184; testing stage. Although, had better performance, however, CART could be considered effective approaches