From data to interpretable models: machine learning for soil moisture forecasting

HIGHLIGHTS

• who: Aniruddha Basak from the Carnegie Mellon University, Pittsburgh, USA have published the Article: From data to interpretable models: machine learning for soil moisture forecasting, in the Journal: (JOURNAL) of 19/Dec/2007
• what: The authors focus on hillslope soil moisture response to rainfall, not on rainfall forecasting, as several well-established rainfall forecasting methods exist . The authors show the distinction in the pseudocode presented in Algorithm 1 and discuss further in Sect 4.4. With model inputs highlighted in circles (blue) and output in squares (green for regular and red for irregular), the authors . . .
  

   

  

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