This study presents novel intelligent modeling of the hydraulic conductivity (k) of sandy soil
by employing machine learning (ML) algorithms ie, artificial neural network (ANN), multi …

As a result of heterogeneity nature of soils and variation in its hydraulic conductivity over
several orders of magnitude for various soil types from fine-grained to coarse-grained soils …

Hydraulic conductivity (K) estimation of porous media is of great significance in contaminant
movement and groundwater investigations. The present study examines the influence of …

Correlations are very significant from the earliest days; in some cases, it is essential as it is
difficult to measure the amount directly, and in other cases it is desirable to ascertain the …

A multiple model integration scheme driven by artificial neural network (ANN)(MM-ANN) was
developed and tested to improve the prediction accuracy of soil hydraulic conductivity (Ks) in …

This study deals with development of artificial neural networks (ANNs) and multiple
regression analysis (MRA) models for determining hydraulic conductivity of fine-grained …

The permeability coefficient of soils is an essential measure for designing geotechnical
construction. The aim of this paper was to select a highest performance and reliable …

The present research introduces the best architecture approach and model for predicting the
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …

Soil permeability is an important parameter for assessment of infiltration, runoff, ground
water, drainage and structures design. In the current research, five different data driven …

Saturated hydraulic conductivity is one of the key parameters in soil physics and
hydrological modeling. This study explores the use of Support Vector Machine (SVM) and a …