Development and application of modeling techniques to estimate the unsaturated hydraulic conductivity

Hybridization of multivariate adaptive regression splines and random forest models with an empirical equation for sediment deposition prediction in open channel flow

(2020) Mir Jafar Sadegh Safari   JOURNAL OF HYDROLOGY

Estimating suspended sediment load with multivariate adaptive regression spline, teaching-learning based optimization, and artificial bee colony models

(2018) Banu Yilmaz et al.   SCIENCE OF THE TOTAL ENVIRONMENT

GIS-based multivariate adaptive regression spline and random forest models for groundwater potential mapping in Iran

(2016) Mohsen Zabihi et al.   Environmental Earth Sciences

Support Vector Machine and regression analysis to predict the field hydraulic conductivity of sandy soil

(2015) Moussa S. Elbisy   KSCE Journal of Civil Engineering

The Effect of Predicting Discharge Coefficient by Neural Network on Increasing the Numerical Modeling Accuracy of Flow Over Side Weir

(2015) Abbas Parsaie et al.   WATER RESOURCES MANAGEMENT

Estimation of Hydraulic Conductivity and Its Uncertainty from Grain-Size Data Using GLUE and Artificial Neural Networks

(2012) Bart Rogiers et al.   Mathematical Geosciences

Prediction of Field Hydraulic Conductivity of Clay Liners Using an Artificial Neural Network and Support Vector Machine

(2011) Sarat Kumar Das et al.   International Journal of Geomechanics

Artificial neural network (ANN) models for determining hydraulic conductivity of compacted fine-grained soils

(2009) Yusuf Erzin et al.   CANADIAN GEOTECHNICAL JOURNAL

A working guide to boosted regression trees

(2008) J. Elith et al.   JOURNAL OF ANIMAL ECOLOGY