{"id":597,"date":"2016-07-18T17:55:18","date_gmt":"2016-07-18T20:55:18","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=597"},"modified":"2016-07-18T17:55:18","modified_gmt":"2016-07-18T20:55:18","slug":"vol10-no2-art4","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol10-no2\/vol10-no2-art4\/","title":{"rendered":"Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes"},"content":{"rendered":"<p><strong>T\u00edtulo:<\/strong> Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes<\/p>\n<p><strong>Autores:<\/strong> Santos, Leonardo Trigueiro dos; Santos Filho, Edgar Leite dos; Coelho, Leandro dos Santos<\/p>\n<p align=\"justify\"><strong>Resumo:<\/strong> A m\u00e1quina de vetor suporte (SVM) \u00e9 uma t\u00e9cnica relativamente recente. A SVM tem se mostrado muito eficiente quando aplicada \u00e0 identifica\u00e7\u00e3o e previs\u00e3o de s\u00e9ries temporais, um importante problema no campo da engenharia. Uma variante deste m\u00e9todo, a m\u00e1quina de vetor suporte \u00e0 m\u00ednimos quadrados (LS-SVM) possui as mesmas caracter\u00edsticas b\u00e1sicas de sua predecessora e possui a vantagem de ser mais adequada ao processamento computacional. A fim de refinar o processo de identifica\u00e7\u00e3o realizado pela LS-SVM o algoritmo de otimiza\u00e7\u00e3o por cardumes (FSS) foi escolhido dado suas caracter\u00edsticas de adequa\u00e7\u00e3o a problemas de dif\u00edcil delimita\u00e7\u00e3o e alta dimensionalidade do espa\u00e7o de busca, como no presente artigo. Os resultados das simula\u00e7\u00f5es baseados no uso combinado do LS-SVM com o FSS s\u00e3o promissores em termos de precis\u00e3o e custo computacional quando aplicados ao \u00edndice EPEA\/ESALQ (Centro de Estudos Avan\u00e7ados em Economia Aplicada\/Escola Superior de Agricultura Luiz Queiroz) da soja.<\/p>\n<p><strong>Palavras-chave:<\/strong> Dan\u00e7a da chuva; jogar sal nas nuvens; inc\u00eandio em florestas; modelo n\u00e3o-linear; adapta\u00e7\u00e3o; aprendizagem<\/p>\n<p><strong>P\u00e1ginas:<\/strong> 8<\/p>\n<p><strong>C\u00f3digo DOI:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol10-no2-art4\">10.21528\/lmln-vol10-no2-art4<\/a><\/p>\n<p><strong>Artigo em PDF:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol10-no2-art4.pdf\" rel=\"\">vol10-no2-art4.pdf<\/a><\/p>\n<p><strong>Arquivo BibTex:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol10-no2-art4.bib\" rel=\"\">vol10-no2-art4.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes Autores: Santos, Leonardo Trigueiro dos; Santos Filho, Edgar Leite dos; Coelho, Leandro dos Santos Resumo: A m\u00e1quina de vetor suporte (SVM) \u00e9 uma t\u00e9cnica relativamente recente. <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol10-no2\/vol10-no2-art4\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":585,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-597","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol10-no2\/vol10-no2-art4\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"T\u00edtulo: Identifica\u00e7\u00e3o e Previs\u00e3o de S\u00e9ries Temporais Utilizando LS-SVM Otimizado pelo Algoritmo de Cardumes Autores: Santos, Leonardo Trigueiro dos; Santos Filho, Edgar Leite dos; Coelho, Leandro dos Santos Resumo: A m\u00e1quina de vetor suporte (SVM) \u00e9 uma t\u00e9cnica relativamente recente. 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