<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>plutao.sid.inpe.br 800</site>
		<holdercode>{isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}</holdercode>
		<identifier>J8LNKAN8RW/3D53LKN</identifier>
		<repository>dpi.inpe.br/plutao/2012/11.28.16.47.53</repository>
		<lastupdate>2015:03.16.17.06.52 dpi.inpe.br/plutao@80/2008/08.19.15.01 administrator</lastupdate>
		<metadatarepository>dpi.inpe.br/plutao/2012/11.28.16.47.54</metadatarepository>
		<metadatalastupdate>2018:06.05.00.02.06 dpi.inpe.br/plutao@80/2008/08.19.15.01 administrator {D 2012}</metadatalastupdate>
		<secondarykey>INPE--PRE/</secondarykey>
		<label>lattes: 2720072834057575 2 SambattiAnLuCaShCa:2012:AuCoNe</label>
		<citationkey>SambattiAnLuCaShCa:2012:AuCoNe</citationkey>
		<title>Automatic con&#64257;guration for neural network applied to atmospheric temperature pro&#64257;le identi&#64257;cation</title>
		<year>2012</year>
		<secondarytype>PRE CI</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>135 KiB</size>
		<author>Sambatti, Sabrina Bergoch Monteiro,</author>
		<author>Anochi, Juliana Aparecida,</author>
		<author>Luz, Eduardo Fávero Pacheco da,</author>
		<author>Carvalho, Adenilson R.,</author>
		<author>Shiguemori, Elcio Hideiti,</author>
		<author>Campos Velho, Haroldo Fraga de,</author>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid>8JMKD3MGP5W/3C9JHC3</resumeid>
		<group>LAC-CTE-INPE-MCTI-GOV-BR</group>
		<group>LAC-CTE-INPE-MCTI-GOV-BR</group>
		<group>LAC-CTE-INPE-MCTI-GOV-BR</group>
		<group></group>
		<group></group>
		<group>LAC-CTE-INPE-MCTI-GOV-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>SERPRO</affiliation>
		<affiliation>Instituto de Estudos Avançado (IEAv)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>sabrinabms@gmail.com</electronicmailaddress>
		<electronicmailaddress>juliana.anochi@lac.inpe.br</electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress>haroldo@lac.inpe.br</electronicmailaddress>
		<e-mailaddress>juliana.anochi@lac.inpe.br</e-mailaddress>
		<conferencename>International Conference on Engineering Optimization (EngOpt).</conferencename>
		<conferencelocation>Rio de Janeiro - RJ</conferencelocation>
		<date>2012</date>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<versiontype>publisher</versiontype>
		<keywords>Atmospheric temperature profile, artificial neural network, optimized topology, inverse problem.</keywords>
		<abstract>Multi-particle collision algorithm (MPCA) is applied to design an optimum architecture for a supervised ANN. The MPCA optimization algorithm emulates a collision process of multiple particles inspired in processes of a neutron traveling in a nuclear reactor. The procedure to carry out the automatic configuration for multi-layer perceptron (MLP) neural network is applied to identify the vertical temperature profiles are obtained from measured satellite radiance data. The MLP-NN is trained with data provided by the direct model characterized by the Radiative Transfer Equation (RTE). The MLP-NN results are compared to the ones computed using regularized inverse solutions. In addition to synthetic data (corrupted by noise), real radiation data from the HIRS/2 (High Resolution Infrared Radiation Sounder) is used as input for the MLP-NN to generate temperature profiles that are compared with the temperature profiles measured by a radiosonde. The comparison between the results obtined with automatic process and previous configuration chosen by an expert is evaluated.</abstract>
		<area>COMP</area>
		<language>en</language>
		<targetfile>sambatti_automatic.pdf</targetfile>
		<usergroup>lattes</usergroup>
		<usergroup>marciana</usergroup>
		<readergroup>administrator</readergroup>
		<readergroup>marciana</readergroup>
		<visibility>shown</visibility>
		<readpermission>allow from all</readpermission>
		<documentstage>not transferred</documentstage>
		<nexthigherunit>8JMKD3MGPCW/3ESGTTP</nexthigherunit>
		<citingitemlist>sid.inpe.br/mtc-m21/2012/07.13.14.49.40 2</citingitemlist>
		<citingitemlist>sid.inpe.br/bibdigital/2013/09.22.23.14 1</citingitemlist>
		<hostcollection>dpi.inpe.br/plutao@80/2008/08.19.15.01</hostcollection>
		<username>marciana</username>
		<lasthostcollection>dpi.inpe.br/plutao@80/2008/08.19.15.01</lasthostcollection>
		<url>http://plutao.sid.inpe.br/rep-/dpi.inpe.br/plutao/2012/11.28.16.47.53</url>
	</metadata>
</metadatalist>