River Water Salinity Prediction Using Hybrid Machine Learning Models Article

Melesse, Assefa M, Khosravi, Khabat, Tiefenbacher, John P et al. (2020). River Water Salinity Prediction Using Hybrid Machine Learning Models . 12(10), 10.3390/w12102951

Open Access International Collaboration

cited authors

  • Melesse, Assefa M; Khosravi, Khabat; Tiefenbacher, John P; Heddam, Salim; Kim, Sungwon; Mosavi, Amir; Pham, Binh Thai

sustainable development goals

authors

publication date

  • October 1, 2020

keywords

  • ARTIFICIAL NEURAL-NETWORKS
  • DATA MINING MODELS
  • DISSOLVED-OXYGEN
  • ELECTRICAL-CONDUCTIVITY
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • FUZZY INFERENCE SYSTEM
  • GROUNDWATER
  • Life Sciences & Biomedicine
  • PERFORMANCE
  • Physical Sciences
  • RANDOM SUBSPACE ENSEMBLES
  • REGRESSION
  • SUPPORT VECTOR MACHINES
  • Science & Technology
  • Water Resources
  • bagging
  • big data
  • data science
  • electrical conductivity
  • hydroinformatics
  • hydrological model
  • machine learning
  • random forest
  • random subspace
  • water salinity

Digital Object Identifier (DOI)

publisher

  • MDPI

volume

  • 12

issue

  • 10