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dc.date.accessioned 2012-11-05T12:24:28Z
dc.date.available 2012-11-05T12:24:28Z
dc.date.issued 2012-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23592
dc.description.abstract 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. en
dc.language en es
dc.subject Intelligent agents es
dc.subject artificial neural network en
dc.subject particulate matter en
dc.subject Neural nets es
dc.subject PM10 en
dc.subject forecast model en
dc.title Prediction of PM10 concentrations for Bahía Blanca, Argentina en
dc.type Objeto de conferencia es
sedici.creator.person Brignole, Nélida B. es
sedici.creator.person Chiarvetto Peralta, Lucila L. es
sedici.creator.person Díaz, Mónica F. es
sedici.description.note Eje: Workshop Agentes y sistemas inteligentes (WASI) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2012-10
sedici.relation.event XVIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)