{"id":1435,"date":"2022-09-01T23:16:29","date_gmt":"2022-09-01T23:16:29","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1435"},"modified":"2022-09-01T23:16:29","modified_gmt":"2022-09-01T23:16:29","slug":"vol19-no1-art3","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/","title":{"rendered":"Sobre o Problema de Previs\u00e3o da Covid-19 Utilizando Modelos Morfol\u00f3gico-Linear Profundos"},"content":{"rendered":"<p>Ricardo de Andrade Ara\u00fajo <a href=\"https:\/\/orcid.org\/0000-0001-6175-4250\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> The coronavirus disease 2019 (COVID-19) has been declared by the World Health Organization (WHO) as an unprecedented pandemic in the present days, straining healthcare systems due to the high demand for admissions to intensive care units. In this context, estimating the dynamics of the COVID19 pandemic is essential to deal with health system drawbacks. Therefore, in this work we developed an empirical study on time series related to the COVID-19 pandemic and, based on this study, we present a deep morphological-linear model, trained by a gradient-based learning process, able to predict this particular kind of time series. Trying to assess the predictive performance of the proposed model, we use daily COVID-19 time series in Brazil and United States of America. The achieved results show that the proposed model outperforms classical and recent machine learning models to estimate the dynamics of the COVID-19 pandemic.<\/p>\n<p><strong>Keywords:<\/strong> COVID-19, Time Series, Prediction, Morphological-Linear model, Deep Learning.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol19-no1-art3\">10.21528\/lnlm-vol19-no1-art3<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/12\/vol19-no1-art3.pdf\">vol19-no1-art3.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/12\/vol19-no1-art3.bib\">vol19-no1-art3.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ricardo de Andrade Ara\u00fajo Abstract: The coronavirus disease 2019 (COVID-19) has been declared by the World Health Organization (WHO) as an unprecedented pandemic in the present days, straining healthcare systems due to the high demand for admissions to intensive care <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1380,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1435","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>Sobre o Problema de Previs\u00e3o da Covid-19 Utilizando Modelos Morfol\u00f3gico-Linear Profundos - 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\/vol19-no1\/vol19-no1-art3\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Sobre o Problema de Previs\u00e3o da Covid-19 Utilizando Modelos Morfol\u00f3gico-Linear Profundos - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Ricardo de Andrade Ara\u00fajo Abstract: The coronavirus disease 2019 (COVID-19) has been declared by the World Health Organization (WHO) as an unprecedented pandemic in the present days, straining healthcare systems due to the high demand for admissions to intensive care Read More ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/\" \/>\n<meta property=\"og:site_name\" content=\"Learning and NonLinear Models\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minuto\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/\",\"name\":\"Sobre o Problema de Previs\u00e3o da Covid-19 Utilizando Modelos Morfol\u00f3gico-Linear Profundos - Learning and NonLinear Models\",\"isPartOf\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"datePublished\":\"2022-09-01T23:16:29+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/#primaryimage\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no1\/vol19-no1-art3\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Browse issues\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Learning &#038; 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