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Memorias de investigación
Communications at congresses:
Pollution Alarm System in Mexico
Year:2009
Research Areas
  • Processing and signal analysis
Information
Abstract
Air pollution is one of the most important environmental problems. The prediction of air pollutant concentrations would allow taking preventive measures such as reducing the pollutant emission to the atmosphere. This paper presents a pollution alarm system used to predict the air pollution concentrations in Salamanca, Mexico. The work focuses on the daily maximum concentration of PM10. A Feed Forward Neural Network has been used to make the prediction. A database used to train the Neural Network corresponds to historical time series of meteorological variables (wind speed, wind direction, temperature and relative humidity) and air pollutant concentrations of PM10 along a year. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of PM10 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
International
Si
Congress
IWANN 2009
960
Place
Salamanca, España
Reviewers
Si
ISBN/ISSN
978-3-642-02477-1
10.1007/978-3-642-02478-8_167
Start Date
10/06/2009
End Date
12/06/2009
From page
1336
To page
1343
Bio-Inspired Systems : Computational and Ambient Intelligence (IWANN 039;09). LCNS 5517
Participants
  • Autor: Antonio Vega-Corona (UDG)
  • Autor: María Guadalupe Cortina Januchs (UPM)
  • Autor: Jose Miguel Barron Adame (UPM)
  • Autor: Diego Andina De la Fuente (UPM)
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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