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Memorias de investigación
Communications at congresses:
ANN and Fuzzy c-Means applied to environmental pollution prediction
Year:2012
Research Areas
  • Engineering
Information
Abstract
Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.
International
Si
Congress
World Automation Congress (WAC), 2012
960
Place
Puerto Vallarta, Mexico
Reviewers
Si
ISBN/ISSN
2154-4824
Start Date
24/06/2012
End Date
28/06/2012
From page
1
To page
6
World Automation Congress (WAC), 2012
Participants
  • Autor: María Guadalupe Cortina Januchs (UPM)
  • Autor: Joel Quintanilla Dominguez (UPM)
  • Autor: Diego Andina De la Fuente (UPM)
  • Autor: Antonio Vega-Corona (Univ. Gto.)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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