{"id":145481,"date":"1993-01-01T00:00:00","date_gmt":"1993-01-01T00:00:00","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/aproximacion-a-los-sistemas-borrosos-y-neuronales-como-ayuda-al-proceso-de-toma-de-decisiones-en-inversion-financiera\/"},"modified":"1993-01-01T00:00:00","modified_gmt":"1993-01-01T00:00:00","slug":"aproximacion-a-los-sistemas-borrosos-y-neuronales-como-ayuda-al-proceso-de-toma-de-decisiones-en-inversion-financiera","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/ciencias-economicas\/aproximacion-a-los-sistemas-borrosos-y-neuronales-como-ayuda-al-proceso-de-toma-de-decisiones-en-inversion-financiera\/","title":{"rendered":"Aproximacion a los sistemas borrosos y neuronales, como ayuda al proceso de toma de decisiones en inversion financiera."},"content":{"rendered":"<h2>Tesis doctoral de <strong> Hilarion Mu\u00f1oz Contreras <\/strong><\/h2>\n<p>El trabajo realiza una aproximacion a los sistemas neuronales y a los borrosos tratandolos mediante supercomputacion, para valorar la ayuda que puedan prestar al proceso de toma de decisiones en inversion financiera y lograr una mejor gestion de la incertidumbre. Primeramente, bajo los fundamentos de la logica borrosa condicional: si a, entonces b, y la teoria de agrupacion del producto-espacio input-output para generar reglas fam (fuzzy associative memory), a partir de muestras preparadas de datos en el hipercubo rn, e implementando el algoritmo respectivo, procesamos informacion bursatil con la finalidad de obtener un valor de \u00abprediccion.\u00bb posteriormente, tambien fundamentados en los principios y caracteristicas de los sistemas neuronales, sobre todo por sus capacidades de generalizacion, y aprendizaje mediante ejemplos suministrados a traves de muestras de datos, buscamos obtener por la implementacion del algoritmo backpropagation un valor output de \u00abprediccion\u00bb. Ambos sistemas se procesan separadamente en su superordenador: ibm 3090\/600j.  finalmente, se valoran los resultados de \u00abprediccion\u00bb obtenidos, la realizacion de los sistemas respectivos para cada caso y se sacan las conclusiones siguientes:- los sistemas borrosos se comportan como neuronales y los neuronales como borrosos.  -el superordenador es un instrumento util y eficaz para apoyar el proceso de toma de decisiones bajo incertidumbre.- Ambos sistemas son un paradigma eficaz para encontrar relaciones causales entre datos.- Los dos sistemas son una alternativa viable a los metodos clasicos usuales para gestionar la incertidumbre.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Aproximacion a los sistemas borrosos y neuronales, como ayuda al proceso de toma de decisiones en inversion financiera.<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Aproximacion a los sistemas borrosos y neuronales, como ayuda al proceso de toma de decisiones en inversion financiera. <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Hilarion Mu\u00f1oz Contreras <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de catalunya<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 01\/01\/1993<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Miquel Subirachs Torn\u00e9<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Josep Mar\u00eda Fonts Boronat <\/li>\n<li>Francisco Tarrago Sabate (vocal)<\/li>\n<li>Jaume Gil Aluja (vocal)<\/li>\n<li>Llu\u00eds Garrido Beltr\u00e1n (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Hilarion Mu\u00f1oz Contreras El trabajo realiza una aproximacion a los sistemas neuronales y a los borrosos tratandolos [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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