Memorias de investigación
Ponencias en congresos:
ANN and Fuzzy c-Means applied to environmental pollution prediction
Año:2012
Áreas de investigación
  • Ingenierías
Datos
Descripción
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.
Internacional
Si
Nombre congreso
World Automation Congress (WAC), 2012
Tipo de participación
960
Lugar del congreso
Puerto Vallarta, Mexico
Revisores
Si
ISBN o ISSN
2154-4824
DOI
Fecha inicio congreso
24/06/2012
Fecha fin congreso
28/06/2012
Desde la página
1
Hasta la página
6
Título de las actas
World Automation Congress (WAC), 2012
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: María Guadalupe Cortina Januchs UPM
  • Autor: Joel Quintanilla Dominguez UPM
  • Autor: Diego Andina De la Fuente UPM
  • Autor: Antonio Vega-Corona Univ. Gto.
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones