Multistep-ahead daily inflow forecasting using the era-interim reanalysis data set based on gradient-boosting regression trees

HIGHLIGHTS

• who: Hydrol. Earth Syst. Sci. and colleagues from the Institute of Hydropower System and Hydroinformatics, Dalian University of Technology, Dalian, China have published the research: Multistep-ahead daily inflow forecasting using the ERA-Interim reanalysis data set based on gradient-boosting regression trees, in the Journal: (JOURNAL) of 31/Dec/2018
• what: In this study a new hybrid inflow forecast framework - using the ERA-Interim reanalysis data set as input and adopting gradient-boosting regression trees (GBRT) and the maximal information coefficient (MIC) - is developed for multistep-ahead daily inflow forecasting. In this study, GBRT . . .
  

   

  

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