Analysis of atmospheric pollutant data using self-organizing maps

HIGHLIGHTS

  • who: Emanoel L. R. Costa and colleagues from the Laboratory of Machine Learning and Intelligent Instrumentation, Federal University of Rio Grande do Norte, Natal, RN, Brazil have published the article: Analysis of Atmospheric Pollutant Data Using Self-Organizing Maps, in the Journal: Sustainability 2022, 14, 10369. of 19/06/2011
  • what: This work proposes an SOM implementation to study and analyze atmospheric pollutants to identify their patterns and characteristics.
  • how: The study carried out used the SOM to highlight the impact on air quality caused by the circulation of different air types which . . .

     

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