Random forest, M5P and regression analysis to estimate the field unsaturated hydraulic conductivity
Hydraulic conductivity of soil reveals its influencing role in the studies related to
management of surface and subsurface flow, eg irrigation and drainage projects, and solute …
management of surface and subsurface flow, eg irrigation and drainage projects, and solute …
Prediction of unsaturated hydraulic conductivity using fuzzy logic and artificial neural network
P Sihag - Modeling Earth Systems and Environment, 2018 - Springer
Abstract Knowledge of hydraulic properties is necessary for hydrological studies, artificial
recharge of the aquifer, watershed management and agriculture system. The major objective …
recharge of the aquifer, watershed management and agriculture system. The major objective …
Understanding the exchange process between ground and surface water using mini drive point piezometer and mathematical models to identify suitable managed …
In the current study, subsurface characteristics within the complex formation of the Shilabati
basin system of West Bengal, India, extending over an area of 3888 km2, have been …
basin system of West Bengal, India, extending over an area of 3888 km2, have been …
Implementation and efficient evaluation of backpropagation network training algorithms in parametric simulations of soil hydraulic conductivity curve
The estimation of the soil hydraulic conductivity curve (SHCC) through machine learning
tools for determining pedotransfer functions (PTFs) is essential in various agriculture …
tools for determining pedotransfer functions (PTFs) is essential in various agriculture …
Predicting Earth-Vas2 parameters of coastal plain sand aquifers using artificial neural Network (s), in the Calabar region of Nigeria
This study employs artificial neural networks (ANNs), specifically the Nonlinear
Autoregressive with External Input (NARX) model as an ANN add-on for Matlab, to forecast …
Autoregressive with External Input (NARX) model as an ANN add-on for Matlab, to forecast …
Machine learning-based modeling of saturated hydraulic conductivity in soils of tropical semi-arid zone of India
Saturated hydraulic conductivity (Kfs) is the major parameter that affects the movement of
water and solutes in soil strata. Although one can estimate the Kfs directly by using various …
water and solutes in soil strata. Although one can estimate the Kfs directly by using various …
Modeling of UCS value of stabilized pond ashes using adaptive neuro-fuzzy inference system and artificial neural network
M Suthar - Soft Computing, 2020 - Springer
This paper investigates the capability of adaptive neuro-fuzzy inference system (ANFIS) and
artificial neural network (ANN) modeling approach to predict the unconfined compressive …
artificial neural network (ANN) modeling approach to predict the unconfined compressive …
Prediction of aquifer properties from vertical electrical sounding data using artificial neural network: case study of Ibadan Metropolis, South-western Nigeria
Adequate estimates of aquifer properties are of utmost importance for proper management
of groundwater resources. In an effort to provide alternative way of estimating aquifer …
of groundwater resources. In an effort to provide alternative way of estimating aquifer …
[HTML][HTML] Proposta de um método alternativo para a estimativa da condutividade hidráulica em solos não saturados
JPO Silva, SA Dantas Neto… - Matéria (Rio de Janeiro), 2022 - SciELO Brasil
RESUMO A determinação da condutividade hidráulica em solos não saturados é essencial
ao realizar análises de fluxo transiente nesses meios porosos. No entanto, a execução de …
ao realizar análises de fluxo transiente nesses meios porosos. No entanto, a execução de …
Determination of unsaturated hydraulic conductivity at field conditions and mathematical modeling.
The objective of this study was to determine the unsaturated soil hydraulic conductivity in the
heavily structured Arıklı soil series with 37o00'53" N and 35o21'24" S coordinates and to …
heavily structured Arıklı soil series with 37o00'53" N and 35o21'24" S coordinates and to …