Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Forecasting SO2 Air Pollution in Salamanca, Mexico using an ADALINE
Year:2008
Research Areas
  • Artificial intelligence,
  • Automatic,
  • Processing and signal analysis
Information
Abstract
A comparison between a linear regression model and a Non-linear regressionmodel is presented in this work for forecasting of pollution levels due to SO2 in Salamanca city, Gto. Prediction is performed by means of an Adaptive Linear Neural Network (ADALINE) and a Generalized Regression NeuralNetwork (GRNN). Prediction experiments are realized for 1, 12 and 24 hours in advance, and the results for linear regression have been satisfactory. The performance estimation of both models are determined using the Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Obtained results are compared. The final results indicated that ADALINE outperforms the past approach using GRNN.
International
Si
Congress
Proceedings of the 5th Virtual International conference on Intelligent Production Machines and Systems, I*$PROMS 2009. te anexo la publicación, saludos
960
Place
Virtual
Reviewers
Si
ISBN/ISSN
978-1-904445-81-4
Start Date
01/07/2008
End Date
14/07/2008
From page
232
To page
237
Innovative Production Machines and Systems. D.T. Pham, E.E. Eldukhri and A.J. Soroka (eds) © 2008 MEC. Cardiff University, UK.
Participants
  • Autor: US Mendoza (Universidad de Guanajuato, Facultad de Ingeniería Mecánica, Eléctrica y Electrónica, México.)
  • Autor: María Guadalupe Cortina Januchs (UPM)
  • Autor: Jose Miguel Barron Adame (UPM)
  • Autor: A Vega-Corona (Universidad de Guanajuato, Facultad de Ingeniería Mecánica, Eléctrica y Electrónica, México.)
  • 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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