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		<citationkey>VelhoHärt:2009:PrReNe</citationkey>
		<title>Preliminary results with neural network for data assimilation to the space weather</title>
		<format>On-line</format>
		<project>Brazilian Decimetric Array</project>
		<year>2009</year>
		<date>July 28 ¨C August 1, 2008</date>
		<numberoffiles>1</numberoffiles>
		<size>177 KiB</size>
		<author>Velho, Haroldo de Campos,</author>
		<author>Härter, Fabrício P.,</author>
		<group>LAC-CTE-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>National Institute of Meteorology (INMet)</affiliation>
		<electronicmailaddress>haroldo@lac.inpe.br</electronicmailaddress>
		<electronicmailaddress>fabricio.harter@inmet.gov.br</electronicmailaddress>
		<editor>Scientific,</editor>
		<editor>Sawant, Hanumant Shankar,</editor>
		<editor>Rao, A. Pramesh,</editor>
		<editor>Gopalswamy, Natchimuthukonar,</editor>
		<editor>Hurford, Gordon J.,</editor>
		<editor>Ananthakrishnan, Subramaniam,</editor>
		<editor>Executive,</editor>
		<editor>Fernandes, Francisco Carlos Rocha,</editor>
		<editor>Moraes, Lu¨ªs Cesar Pereira de,</editor>
		<e-mailaddress>lcmoraes@das.inpe.br</e-mailaddress>
		<conferencename>Brazilian Decimetric Array Workshop.</conferencename>
		<conferencelocation>INPE</conferencelocation>
		<pages>161-168</pages>
		<booktitle>Proceedings</booktitle>
		<publisher>INPE</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<secondarytype>PRE CI</secondarytype>
		<tertiarytype>Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>NEURAL, NETWORK, ASSIMILATION, SPACE, WEATHER.</keywords>
		<abstract>Data assimilation is an essential step for improving space weather operational forecasting by means of an appropriated combination between observational data and data from a mathematical model. In the present work data assimilation methods based on Kalman filter and artificial neural networks are applied to a three-wave model of auroral radio emissions. A novel data assimilation method is presented, whereby a multilayer perceptron neural network is trained to emulate a Kalman filter for data assimilation by using cross validation. The results obtained render support for the use of neural networks as an assimilation technique for space weather prediction.</abstract>
		<area>CEA</area>
		<language>en</language>
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		<url>http://mtc-m16c.sid.inpe.br/rep-/sid.inpe.br/mtc-m18@80/2009/07.16.16.36</url>
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