Using machine learning-based variable selection to identify hydrate related components from ft-icr ms spectra

HIGHLIGHTS

• who: Elise Lunde Gjelsvik and collaborators from the Norwegian University of Life Sciences, Faculty of Science and Technology, Aas, SINTEF AS have published the research: Using machine learning-based variable selection to identify hydrate related components from FT-ICR MS spectra, in the Journal: PLOS ONE of 17/08/2022
• what: This work describes the use of machine_learning-based variable selection for the identification of naturally occurring hydrate inhibitors from ESI positive FT-ICR MS spectra and relating the selected variables to the wettability state of the respective crude oils. In this paper, variable selection . . .
  

   

  

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