Prediction of PM10 concentrations for Bahía Blanca, Argentina
- Autores
- Brignole, Nélida B.; Chiarvetto Peralta, Lucila L.; Díaz, Mónica F.
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- PM10 non-traditional modelling for e-government development is described in detail. Ambient PM10 concentrations were predicted using meteorological variables as inputs, whose relevance for a generated Artificial Neural Network was analyzed by a feature selection method. The work is specially focused on the surroundings of Bahía Blanca city, its petrochemical pole and Ing. White grain port. Its accuracy was tested with time windows ranging from 2004 to 2006. A trustworthy simulation of the physical phenomena was built. As a result, this predictive model will contribute to the local observatory in order to trigger early-alert warnings.
Eje: Workshop Agentes y sistemas inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Intelligent agents
Neural nets
artificial neural network
particulate matter
PM10
forecast model - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23592
Ver los metadatos del registro completo
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Prediction of PM10 concentrations for Bahía Blanca, ArgentinaBrignole, Nélida B.Chiarvetto Peralta, Lucila L.Díaz, Mónica F.Ciencias InformáticasIntelligent agentsNeural netsartificial neural networkparticulate matterPM10forecast modelPM10 non-traditional modelling for e-government development is described in detail. Ambient PM10 concentrations were predicted using meteorological variables as inputs, whose relevance for a generated Artificial Neural Network was analyzed by a feature selection method. The work is specially focused on the surroundings of Bahía Blanca city, its petrochemical pole and Ing. White grain port. Its accuracy was tested with time windows ranging from 2004 to 2006. A trustworthy simulation of the physical phenomena was built. As a result, this predictive model will contribute to the local observatory in order to trigger early-alert warnings.Eje: Workshop Agentes y sistemas inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2012-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23592enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:31Zoai:sedici.unlp.edu.ar:10915/23592Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:31.562SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
title |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
spellingShingle |
Prediction of PM10 concentrations for Bahía Blanca, Argentina Brignole, Nélida B. Ciencias Informáticas Intelligent agents Neural nets artificial neural network particulate matter PM10 forecast model |
title_short |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
title_full |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
title_fullStr |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
title_full_unstemmed |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
title_sort |
Prediction of PM10 concentrations for Bahía Blanca, Argentina |
dc.creator.none.fl_str_mv |
Brignole, Nélida B. Chiarvetto Peralta, Lucila L. Díaz, Mónica F. |
author |
Brignole, Nélida B. |
author_facet |
Brignole, Nélida B. Chiarvetto Peralta, Lucila L. Díaz, Mónica F. |
author_role |
author |
author2 |
Chiarvetto Peralta, Lucila L. Díaz, Mónica F. |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Intelligent agents Neural nets artificial neural network particulate matter PM10 forecast model |
topic |
Ciencias Informáticas Intelligent agents Neural nets artificial neural network particulate matter PM10 forecast model |
dc.description.none.fl_txt_mv |
PM10 non-traditional modelling for e-government development is described in detail. Ambient PM10 concentrations were predicted using meteorological variables as inputs, whose relevance for a generated Artificial Neural Network was analyzed by a feature selection method. The work is specially focused on the surroundings of Bahía Blanca city, its petrochemical pole and Ing. White grain port. Its accuracy was tested with time windows ranging from 2004 to 2006. A trustworthy simulation of the physical phenomena was built. As a result, this predictive model will contribute to the local observatory in order to trigger early-alert warnings. Eje: Workshop Agentes y sistemas inteligentes (WASI) Red de Universidades con Carreras en Informática (RedUNCI) |
description |
PM10 non-traditional modelling for e-government development is described in detail. Ambient PM10 concentrations were predicted using meteorological variables as inputs, whose relevance for a generated Artificial Neural Network was analyzed by a feature selection method. The work is specially focused on the surroundings of Bahía Blanca city, its petrochemical pole and Ing. White grain port. Its accuracy was tested with time windows ranging from 2004 to 2006. A trustworthy simulation of the physical phenomena was built. As a result, this predictive model will contribute to the local observatory in order to trigger early-alert warnings. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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http://sedici.unlp.edu.ar/handle/10915/23592 |
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http://sedici.unlp.edu.ar/handle/10915/23592 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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