Data completion, model correction and enrichment based on sparse identification and data assimilation

HIGHLIGHTS

• who: Daniele Di Lorenzo et al. from the bis Rue Saarinen, , Rungis, France Aragon Institute of Engineering Research, Universidad de Zaragoza, Maria de Luna s/n have published the paper: Data Completion, Model Correction and Enrichment Based on Sparse Identification and Data Assimilation, in the Journal: (JOURNAL) of 25/07/2022
• what: The authors propose a methodology for locally correcting or globally enriching the models from collected which is upon its turn completed beyond the sensor`s location. The question is as follows: Can the authors determine this solution with only three data? In the . . .
  

   

  

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