<?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>0120-419X</journal-id>
<journal-title><![CDATA[Revista Integración]]></journal-title>
<abbrev-journal-title><![CDATA[Integración - UIS]]></abbrev-journal-title>
<issn>0120-419X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Industrial de Santander]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-419X2018000200067</article-id>
<article-id pub-id-type="doi">10.18273/revint.v36n2-2018001</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Solución numérica de un problema inverso aplicando un algoritmo genético continuo]]></article-title>
<article-title xml:lang="en"><![CDATA[Numerical solution of an inverse problem by applying a continuous genetic algorithm]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Berres]]></surname>
<given-names><![CDATA[Stefan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Coronel]]></surname>
<given-names><![CDATA[Aníbal]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lagos]]></surname>
<given-names><![CDATA[Richard]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Católica de Temuco Facultad de Ingeniería Departamento de Ciencias Matemáticas y Físicas]]></institution>
<addr-line><![CDATA[Temuco ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad del Bío Bío Facultad de Ciencias Departamento de Ciencias Básicas]]></institution>
<addr-line><![CDATA[Chillán ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Magallanes Facultad de Ciencias Departamento de Matemática]]></institution>
<addr-line><![CDATA[Punta Arenas ]]></addr-line>
<country>Chile</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<volume>36</volume>
<numero>2</numero>
<fpage>67</fpage>
<lpage>81</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-419X2018000200067&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-419X2018000200067&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-419X2018000200067&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este artículo se considera el problema de la determinación de la función de flujo en una ley de conservación escalar que modela el fenómeno de sedimentación. Los datos de la observación experimental utilizada para la calibración corresponden a un perfil de la concentración de sólidos en un tiempo fijo. El problema de identificación se formula como uno de optimización, donde la función objetivo es la de mínimos cuadrados que minimiza la distancia entre los perfiles solución del modelo y la observación. La solución del problema directo es aproximada por un esquema de volúmenes finitos monótono. La solución numérica del problema de calibración se obtiene mediante un algoritmo genético continuo. Se presentan resultados numéricos para validar la eficiencia del algoritmo propuesto. MSC2010: 90C59, 90C30, 49M20, 35L50, 35L65.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In this paper we consider the problem of flux determination in a scalar conservation law modeling the phenomenon of sedimentation. The experimental observation data used for the calibration consist of a solid concentration profile at a fixed time. The identification problem is formulated as an optimization one, where the distance between the profiles of the model simulation and observation data is minimized by a least squares cost function. The direct problem is approximated by a monotone finite volume scheme.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Algoritmo genético continuo]]></kwd>
<kwd lng="es"><![CDATA[calibración]]></kwd>
<kwd lng="es"><![CDATA[identificación de parámetros]]></kwd>
<kwd lng="es"><![CDATA[sedimentación]]></kwd>
<kwd lng="en"><![CDATA[Continuous genetic algorithm]]></kwd>
<kwd lng="en"><![CDATA[calibration]]></kwd>
<kwd lng="en"><![CDATA[parameter identification]]></kwd>
<kwd lng="en"><![CDATA[sedimentation]]></kwd>
</kwd-group>
</article-meta>
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