<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1390-9274</journal-id>
<journal-title><![CDATA[Estoa. Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca]]></journal-title>
<abbrev-journal-title><![CDATA[Estoa]]></abbrev-journal-title>
<issn>1390-9274</issn>
<publisher>
<publisher-name><![CDATA[Centro de Investigación de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1390-92742017000200039</article-id>
<article-id pub-id-type="doi">10.18537/est.v006.n011.a03</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Metodología de ayuda a la decisión mediante SIG e Inteligencia Artificial: aplicación en la caracterización demográfica de Andalucía a partir de su residencia]]></article-title>
<article-title xml:lang="en"><![CDATA[Methodology of Decision Support through GIS and Artificial Intelligence: Implementation for Demographic Characterization of Andalusia based on Dwelling]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Abarca-Alvarez]]></surname>
<given-names><![CDATA[Francisco Javier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Campos-Sánchez]]></surname>
<given-names><![CDATA[Francisco Sergio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Reinoso-Bellido]]></surname>
<given-names><![CDATA[Rafael]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Granada Departamento de Urbanística y Ordenación del Territorio ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Spain</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Granada Departamento de Urbanística y Ordenación del Territorio ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Spain</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Granada Departamento de Urbanística y Ordenación del Territorio ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Spain</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2017</year>
</pub-date>
<volume>6</volume>
<numero>11</numero>
<fpage>39</fpage>
<lpage>64</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S1390-92742017000200039&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S1390-92742017000200039&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S1390-92742017000200039&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: os Sistemas de Información Geográfica (SIG) han sido ampliamente utilizados para el almacenamiento y gestión de la información territorial, mostrándose especialmente útiles para el análisis y para la verificación de hipótesis previamente formuladas y con componentes espaciales relevantes. Existen metodologías heurísticas que en contextos como los actuales, de sobre-abundancia de datos, permiten evidenciar sus coherencias, sin requerir necesariamente hipótesis o formulaciones previas para generar conocimiento. Se propone el uso combinado de (i) técnicas procedentes de la Inteligencia Artificial, como son las Redes Neuronales Artificiales (ANN) del tipo Mapa Auto-organizado (SOM), que han demostrado ser muy eficaces y robustas clasificando y caracterizando perfiles en los datos; integradas con (ii) técnicas de Machine Learning como son los árboles de decisión, singularmente funcionales en la creación de modelos predictivos e interpretables para formular hipótesis explicativas de los perfiles anteriores a partir de otras variables diferenciadas. La investigación plantea combinar SIG, SOM y árboles de decisión para la construcción de modelos explicativos de los perfiles demográficos y sociales de Andalucía, a partir de datos de bajo coste sobre la dimensión residencial. Se verifica la viabilidad de tales modelos predictivos y su alto valor para la comprensión y para la toma de decisiones sobre tales territorios.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Geographic Information Systems (GIS) have been widely used for the storage and management of territorial information, being especially useful for the analysis and verification of previously formulated hypotheses and coexisting with relevant spatial components. There are heuristic methodologies that, in contexts such as the present one, of data over-abundance, allow showing their coherence, not necessarily requiring hypotheses or previous formulations to generate knowledge. The combined use of (i) Artificial Intelligence techniques such as the Artificial Neural Network (ANN), namely the Self-Organized Maps (SOM), is proposed. They are very effective and robust by classifying and characterizing profiles in the data. They interact with (ii) machine learning techniques such as decision trees, which are singularly functional in the creation of predictive and interpretable models, with the intention of formulating explanatory hypotheses of the previous profiles, working with other different variables. The research proposes the combination of GIS, SOM and decision trees for the construction of explanatory models of the demographic and social profiles of Andalusia, based on low cost data on the residential dimension. The feasibility of such predictive models and their great value for understanding and as decision support on such territories are evaluated satisfactorily.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[árbol de decisión SIG]]></kwd>
<kwd lng="es"><![CDATA[DSS]]></kwd>
<kwd lng="es"><![CDATA[mapa auto-organizado]]></kwd>
<kwd lng="en"><![CDATA[GIS]]></kwd>
<kwd lng="en"><![CDATA[decision tree]]></kwd>
<kwd lng="en"><![CDATA[DSS]]></kwd>
<kwd lng="en"><![CDATA[self-organizing map]]></kwd>
<kwd lng="en"><![CDATA[SOM.]]></kwd>
</kwd-group>
</article-meta>
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