Improving daily stochastic stream flow prediction: comparison of novel hybrid data-mining algorithms Article

Khosravi, Khabat, Golkarian, Ali, Booij, Martijn J et al. (2021). Improving daily stochastic stream flow prediction: comparison of novel hybrid data-mining algorithms . HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 66(9), 1457-1474. 10.1080/02626667.2021.1928673

Open Access International Collaboration

cited authors

  • Khosravi, Khabat; Golkarian, Ali; Booij, Martijn J; Barzegar, Rahim; Sun, Wei; Yaseen, Zaher Mundher; Mosavi, Amir

sustainable development goals

authors

publication date

  • July 4, 2021

published in

keywords

  • ANN
  • ARTIFICIAL NEURAL-NETWORKS
  • Attribute Selected Classifier
  • CATCHMENT
  • ENSEMBLE
  • M5P
  • M5Rule
  • MACHINE LEARNING-METHODS
  • MODEL
  • Physical Sciences
  • RIVER
  • RUNOFF
  • SIMULATION
  • SUPPORT VECTOR MACHINE
  • Science & Technology
  • Taleghan catchment
  • Water Resources
  • bagging
  • data mining
  • random forest
  • streamflow modelling

Digital Object Identifier (DOI)

publisher

  • TAYLOR & FRANCIS LTD

start page

  • 1457

end page

  • 1474

volume

  • 66

issue

  • 9