Use of neural networks in the identification of pollutant concentration scenarios in the city of Rio de Janeiro

Authors

  • Flávia Ribeiro Villela Universidade Federal do Rio de Janeiro - UFRJ
  • Marcos Antonio Cruz Moreira Instituto Federal de Educação, Ciência e Tecnologia Fluminense (IFFluminense, Campus Macaé)

DOI:

https://doi.org/10.19180/2177-4560.v10n22016p67-77

Keywords:

Air pollution. Kohonen Maps. Neural Network.

Abstract

Studies carried out in several countries have reported an association between air pollution and several indicators of morbidity and mortality, even when pollutant concentrations are below standard limits. This work has as geographic place of study the city of Rio de Janeiro,and aims to identify local and global scenarios characterized by high or low pollution days and typical or atypical weather days. It also verifies the associations with the statistical distribution of health event counts. The method used to identify these scenarios was Kohonen topological maps based on neural networks.

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Author Biographies

  • Flávia Ribeiro Villela, Universidade Federal do Rio de Janeiro - UFRJ
    Professora da Universidade Federal do Rio de Janeiro (UFRJ), Macaé/RJ - Brasil. Doutoranda em Engenharia de Reservatório e de Exploração pela Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF).
  • Marcos Antonio Cruz Moreira, Instituto Federal de Educação, Ciência e Tecnologia Fluminense (IFFluminense, Campus Macaé)
    Doutor em Engenharia Elétrica pela Universidade Federal do Rio de Janeiro (UFRJ). Professor do Instituto Federal de Educação, Ciência e Tecnologia Fluminense (IFFluminense, Campus Macaé) - Macaé/RJ – Brasil. 

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Published

30-12-2016

Issue

Vol. 10 No. 2 (2016)

Section

Original articles

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How to Cite

Use of neural networks in the identification of pollutant concentration scenarios in the city of Rio de Janeiro. Boletim do Observatório Ambiental Alberto Ribeiro Lamego, [S. l.], v. 10, n. 2, p. 67–77, 2016. DOI: 10.19180/2177-4560.v10n22016p67-77. Disponível em: https://editoraessentia.iff.edu.br/index.php/boletim/article/view/9319.. Acesso em: 21 nov. 2024.

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