{"id":5860,"date":"2023-03-03T14:37:56","date_gmt":"2023-03-03T14:37:56","guid":{"rendered":"https:\/\/aaep.org.ar\/?p=5860"},"modified":"2023-03-03T14:37:58","modified_gmt":"2023-03-03T14:37:58","slug":"una-metodologia-de-clustering-para-agrupar-series-temporales-en-regiones-contiguas","status":"publish","type":"post","link":"https:\/\/aaep.org.ar\/?p=5860","title":{"rendered":"Una metodolog\u00eda de clustering para agrupar series temporales en regiones contiguas"},"content":{"rendered":"<iframe loading=\"lazy\" class=\"wonderplugin-pdf-iframe\" src=\"https:\/\/aaep.org.ar\/wp-content\/plugins\/wonderplugin-pdf-embed\/pdfjslight\/web\/viewer.html?v=2&file=https:\/\/aaep.org.ar\/works\/works2022\/4589.pdf\" width=\"100%\" height=\"600px\" style=\"border:0;\"><\/iframe>\n","protected":false},"excerpt":{"rendered":"<p>Los algoritmos de clustering con restricci\u00f3n espacial existentes est\u00e1n enfocados principalmente en obtener regiones contiguas, pero no hay muchos trabajos que contemplen la agrupaci\u00f3n de series temporales. En este paper se propone una nueva metodolog\u00eda de regionalizaci\u00f3n que contempla los avances que se vienen haciendo en el campo de redes neuronales y aprendizaje no supervisado denominada spatial constraints into deep embedding clustering (SDEC). El prop\u00f3sito del algoritmo es agrupar unidades espaciales transformando el espacio de atributos en otro de menor dimensi\u00f3n representado por variables latentes que logren destacar la caracter\u00edstica del grupo al que pertenecen. Se realizaron simulaciones de series temporales por cada unidad espacial en d\u00f3nde, SDEC muestra resultados superiores con respecto a otros m\u00e9todos existentes en la literatura. Con el objetivo de aplicar el m\u00e9todo a problemas de la vida real, se hace un breve estudio de la evoluci\u00f3n del virus del Covid 19 por departamento o partido de la Rep\u00fablica Argentina, posteriormente se trata de llegar a una interpretaci\u00f3n de los resultados obtenidos para evaluar el funcionamiento del algoritmo.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[29],"tags":[30],"class_list":["post-5860","post","type-post","status-publish","format-standard","hentry","category-anales","tag-aaep-anales-2022"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Una metodolog\u00eda de clustering para agrupar series temporales en regiones contiguas - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Una metodolog\u00eda de clustering para agrupar series temporales en regiones contiguas - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"og:description\" content=\"Los algoritmos de clustering con restricci\u00f3n espacial existentes est\u00e1n enfocados principalmente en obtener regiones contiguas, pero no hay muchos trabajos que contemplen la agrupaci\u00f3n de series temporales. En este paper se propone una nueva metodolog\u00eda de regionalizaci\u00f3n que contempla los avances que se vienen haciendo en el campo de redes neuronales y aprendizaje no supervisado denominada spatial constraints into deep embedding clustering (SDEC). El prop\u00f3sito del algoritmo es agrupar unidades espaciales transformando el espacio de atributos en otro de menor dimensi\u00f3n representado por variables latentes que logren destacar la caracter\u00edstica del grupo al que pertenecen. Se realizaron simulaciones de series temporales por cada unidad espacial en d\u00f3nde, SDEC muestra resultados superiores con respecto a otros m\u00e9todos existentes en la literatura. Con el objetivo de aplicar el m\u00e9todo a problemas de la vida real, se hace un breve estudio de la evoluci\u00f3n del virus del Covid 19 por departamento o partido de la Rep\u00fablica Argentina, posteriormente se trata de llegar a una interpretaci\u00f3n de los resultados obtenidos para evaluar el funcionamiento del algoritmo.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/aaep.org.ar\/?p=5860\" \/>\n<meta property=\"og:site_name\" content=\"Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"article:published_time\" content=\"2023-03-03T14:37:56+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-03-03T14:37:58+00:00\" \/>\n<meta name=\"author\" content=\"aaepolitica\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:site\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"aaepolitica\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5860#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5860\"},\"author\":{\"name\":\"aaepolitica\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#\\\/schema\\\/person\\\/7150b747ba20875259c74b2cd177316c\"},\"headline\":\"Una metodolog\u00eda de clustering para agrupar series temporales en regiones contiguas\",\"datePublished\":\"2023-03-03T14:37:56+00:00\",\"dateModified\":\"2023-03-03T14:37:58+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5860\"},\"wordCount\":27,\"publisher\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#organization\"},\"keywords\":[\"AAEP Anales 2022\"],\"articleSection\":[\"Anales\"],\"inLanguage\":\"es\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5860\",\"url\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5860\",\"name\":\"Una metodolog\u00eda de clustering para agrupar series temporales en regiones contiguas - 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