{"id":459,"date":"2016-07-16T19:28:27","date_gmt":"2016-07-16T22:28:27","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=459"},"modified":"2016-07-16T19:28:27","modified_gmt":"2016-07-16T22:28:27","slug":"vol7-no2-art5","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol7-no2\/vol7-no2-art5\/","title":{"rendered":"Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais"},"content":{"rendered":"<p><strong>T\u00edtulo:<\/strong> Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais<\/p>\n<p><strong>Autores:<\/strong> Anochi, Juliana A.; Silva, Jos\u00e9 Demisio S.<\/p>\n<p align=\"justify\"><strong>Resumo:<\/strong> Este trabalho utiliza t\u00e9cnicas de Intelig\u00eancia artificial baseado em um m\u00e9todo de redu\u00e7\u00e3o de atributos, para realiza\u00e7\u00e3o de previs\u00e3o clim\u00e1tica usando um modelo de Rede Neural Artificial. Para o desenvolvimento desta metodologia utilizou-se a Teoria dos Conjuntos Aproximativos para extrair informa\u00e7\u00f5es relevantes dos dados, visando reduzir a redund\u00e2ncia entre as vari\u00e1veis. O processo de previs\u00e3o clim\u00e1tica foi desenvolvido sobre a regi\u00e3o Nordeste do Brasil, para aprender o comportamento sazonal da vari\u00e1vel de precipita\u00e7\u00e3o.<\/p>\n<p><strong>Palavras-chave:<\/strong> Previs\u00e3o Clim\u00e1tica; Teoria dos Conjuntos Aproximativos; Redes Neurais Artificiais<\/p>\n<p><strong>P\u00e1ginas:<\/strong> 9<\/p>\n<p><strong>C\u00f3digo DOI:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol7-no2-art5\">10.21528\/lmln-vol7-no2-art5<\/a><\/p>\n<p><strong>Artigo em PDF:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol7-no2-art5.pdf\" rel=\"\">vol7-no2-art5.pdf<\/a><\/p>\n<p><strong>Arquivo BibTex:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol7-no2-art5.bib\" rel=\"\">vol7-no2-art5.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais Autores: Anochi, Juliana A.; Silva, Jos\u00e9 Demisio S. Resumo: Este trabalho utiliza t\u00e9cnicas de Intelig\u00eancia artificial baseado em um m\u00e9todo de redu\u00e7\u00e3o de <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol7-no2\/vol7-no2-art5\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":449,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-459","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>Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais - 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\/vol7-no2\/vol7-no2-art5\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"T\u00edtulo: Uso de Redes Neurais Artificiais e Teoria de Conjuntos Aproximativos no Estudo de Padr\u00f5es Clim\u00e1ticos Sazonais Autores: Anochi, Juliana A.; Silva, Jos\u00e9 Demisio S. 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