Enhancing the prediction of hydraulic parameters using machine learning, integrating multiple attributes of GIS and geophysics

This publication has 52 references indexed in Scilit:

• Predicting Saturated Hydraulic Conductivity by Artificial Intelligence and Regression Models
  ISRN Soil Science, 2013
• Aquifer hydraulic conductivity estimation from surface geoelectrical measurements for Krauthausen test site, Germany
  Hydrogeology Journal, 2011
• Development of Pedotransfer Functions for Estimation of Soil Hydraulic Parameters using Support Vector Machines
  Soil Science Society of America Journal, 2009
• A Damped Least-Squares Inversion Program for the Interpretation of Schlumberger Sounding Curves
  Journal of Applied Sciences, 2008
• Estimation of aquifer hydraulic parameters from surficial geophysical methods: A case study of Keritis Basin in Chania (Crete – Greece)
  Journal of Hydrology, 2007
• Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction
  Ecosystems, 2006
• Aquifer Parameter Estimation from Surface Resistivity Data
  Groundwater, 2003
• On the profile of random trees
  Random Structures & Algorithms, 1997
• Estimation of aquifer transmissivity from Dar-Zarrouk parameters in porous media
  Journal of Hydrology, 1981
• The Deccan Basalts of Maharashtra, India —Their Potential as Aquifers
  Groundwater, 1980