How can we benefit from regime information to make more effective use of long short-term memory (lstm) runoff models?

HIGHLIGHTS

• who: Hydrol. Earth Syst. Sci. and collaborators from the Aix-Marseille University, RECOVER Research Unit, Aix-en-Provence, France have published the paper: How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?, in the Journal: (JOURNAL) of 31/07/2019
• what: The authors show that LSTM performance has the highest sensitivity to the length of the input sequence in the Uniform and Nival regimes where the dominant hydrologic process of the regime has clear long-term dynamics; thus long input sequences should be chosen . . .
  

   

  

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