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Vega Corona, Antonio, Barron Adame, Jose Miguel, Ibarra Manzano, Óscar Gerardo, Cortina Januchs, María Guadalupe, Quintanilla Domínguez, Joel and Andina de la Fuente, Diego ORCID: https://orcid.org/0000-0001-7036-2646
(2012).
Pollutant concentrations and Meteorological data classification by Neural Networks.
In: "World Automation Congress (WAC), 2012", 24/06/2012 - 28/06/2012, Puerto Vallarta (México). pp. 1-6.
Title: | Pollutant concentrations and Meteorological data classification by Neural Networks |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | World Automation Congress (WAC), 2012 |
Event Dates: | 24/06/2012 - 28/06/2012 |
Event Location: | Puerto Vallarta (México) |
Title of Book: | World Automation Congress (WAC), 2012 |
Date: | 2012 |
Subjects: | |
Faculty: | E.T.S.I. Telecomunicación (UPM) |
Department: | Señales, Sistemas y Radiocomunicaciones |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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This paper present an environmental contingency forecasting tool based on Neural Networks (NN). Forecasting tool analyzes every hour and daily Sulphur Dioxide (SO2) concentrations and Meteorological data time series. Pollutant concentrations and meteorological variables are self-organized applying a Self-organizing Map (SOM) NN in different classes. Classes are used in training phase of a General Regression Neural Network (GRNN) classifier to provide an air quality forecast. In this case a time series set obtained from Environmental Monitoring Network (EMN) of the city of Salamanca, Guanajuato, México is used. Results verify the potential of this method versus other statistical classification methods and also variables correlation is solved.
Item ID: | 19970 |
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DC Identifier: | https://oa.upm.es/19970/ |
OAI Identifier: | oai:oa.upm.es:19970 |
Official URL: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?... |
Deposited by: | Memoria Investigacion |
Deposited on: | 25 Sep 2013 16:50 |
Last Modified: | 21 Apr 2016 22:01 |