Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches Article

Rahmati, Omid, Naghibi, Seyed Amir, Shahabi, Himan et al. (2018). Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches . JOURNAL OF HYDROLOGY, 565 248-261. 10.1016/j.jhydrol.2018.08.027

International Collaboration

cited authors

  • Rahmati, Omid; Naghibi, Seyed Amir; Shahabi, Himan; Dieu, Tien Bui; Pradhan, Biswajeet; Azareh, Ali; Rafiei-Sardooi, Elham; Samani, Aliakbar Nazari; Melesse, Assefa M

sustainable development goals

authors

publication date

  • October 1, 2018

published in

keywords

  • ARTIFICIAL-INTELLIGENCE APPROACH
  • EVIDENTIAL BELIEF FUNCTION
  • Engineering
  • Engineering, Civil
  • FREQUENCY RATIO
  • FUZZY INFERENCE SYSTEM
  • GIS
  • Geology
  • Geosciences, Multidisciplinary
  • Groundwater spring
  • Hybrid model
  • LEARNING-MODELS
  • LOGISTIC-REGRESSION
  • Logistic model tree
  • Physical Sciences
  • Robustness
  • SPATIAL PREDICTION
  • SUPPORT VECTOR MACHINE
  • SUSCEPTIBILITY ASSESSMENT
  • Science & Technology
  • Technology
  • WEIGHTS-OF-EVIDENCE
  • Water Resources

Digital Object Identifier (DOI)

publisher

  • ELSEVIER

start page

  • 248

end page

  • 261

volume

  • 565