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		<label>lattes: 1304704585952173 2 BotelhoFerr:2012:MaMoPr</label>
		<citationkey>BotelhoFerr:2012:MaMoPr</citationkey>
		<title>A mathematical model to predict operating states of satellites</title>
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		<year>2012</year>
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		<author>Botelho, Primavera,</author>
		<author>Ferreira, Maurício Gonçalves Vieira,</author>
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		<group>LAC-CTE-INPE-MCTI-GOV-BR</group>
		<group>CRC-CRC-INPE-MCTI-GOV-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>prima@laser.inpe.br</electronicmailaddress>
		<electronicmailaddress>mauricio@ccs.inpe.br</electronicmailaddress>
		<e-mailaddress>mauricio@ccs.inpe.br</e-mailaddress>
		<conferencename>International Conference on Space Operations, 12 (SpaceOps).</conferencename>
		<conferencelocation>Estocolmo</conferencelocation>
		<date>2012</date>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Paper</tertiarytype>
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		<keywords>mathematical model, artificial intelligence, satellites.</keywords>
		<abstract>The increased on demand from orbiting satellites in operation according to the National Institute for Space Researchs satellite program has motivated continuous improvement safety in the planning of routine operations in order to ensure the integrity of satellites in orbit. Therefore, we propose a mathematical model based on artificial intelligence concepts, which uses algorithms developed for machine learning in the analysis of operational data to predict future states of satellites. The application developed from this data mining predictive model is also presented as an alternative to expensive simulators to perform prediction of satellites operating conditions, reducing costs of control activities of the satellites in orbit.</abstract>
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		<language>en</language>
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		<url>http://www.spaceops2012.org</url>
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