Knowledge discovery using mixed oceanographic data

Authors

  • Mauro Medeiros Barbat Universidade Federal do Rio Grande http://orcid.org/0000-0001-7930-1612
  • Juliano Lauser Coleto Universidade Federal do Rio Grande
  • Mauricio Gayer Goulart Universidade Federal do Rio Grande
  • Eduardo Porto Teixeira Universidade Federal do Rio Grande
  • Karina Machado dos Santos Universidade Federal do Rio Grande
  • Eduardo Nunes Borges Universidade Federal do Rio Grande

DOI:

https://doi.org/10.14808/sci.plena.2015.081326

Keywords:

Knowledge discovery, data mining, oceanography.

Abstract

In oceanographic studies is common the use of different data bases in order to correlate common structures that show evidence of a certain aspect. Like oceanographic and meteorological data obtained through satellites probes and another made available by international research corporations. This paper aims at applying a knowledge extraction process in order to correlate data from remote sensing like ocean temperature and chlorophyll-a levels with fish catch data from fishing companies. More specifically, to correlate the abundance of live resource skipjack tuna (Katsuwonus Pelamis) with these environmental parameters from satellite sensors.

Author Biographies

Mauro Medeiros Barbat, Universidade Federal do Rio Grande

http://lattes.cnpq.br/0160921826651799

Juliano Lauser Coleto, Universidade Federal do Rio Grande

http://lattes.cnpq.br/0441708354036746

Mauricio Gayer Goulart, Universidade Federal do Rio Grande

http://lattes.cnpq.br/9161549144302319

Eduardo Porto Teixeira, Universidade Federal do Rio Grande

http://lattes.cnpq.br/7894543677954950

Karina Machado dos Santos, Universidade Federal do Rio Grande

http://lattes.cnpq.br/3528633359332021

Eduardo Nunes Borges, Universidade Federal do Rio Grande

http://lattes.cnpq.br/5851601274050374

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Published

2015-08-31

How to Cite

Barbat, M. M., Coleto, J. L., Goulart, M. G., Teixeira, E. P., dos Santos, K. M., & Borges, E. N. (2015). Knowledge discovery using mixed oceanographic data. Scientia Plena, 11(8). https://doi.org/10.14808/sci.plena.2015.081326

Issue

Vol. 11 No. 8 (2015): August/Agosto 2015

Section

VI Conferência Sul em Modelagem Computacional

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