<?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>1405-7425</journal-id>
<journal-title><![CDATA[Papeles de población]]></journal-title>
<abbrev-journal-title><![CDATA[Pap. poblac]]></abbrev-journal-title>
<issn>1405-7425</issn>
<publisher>
<publisher-name><![CDATA[Universidad Autónoma del Estado de México, Centro de Investigación y Estudios Avanzados de la Población]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-74252018000100273</article-id>
<article-id pub-id-type="doi">10.22185/24487147.2018.95.11</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[El uso de lógica difusa en proyecciones de población: el caso de México]]></article-title>
<article-title xml:lang="en"><![CDATA[The use of fuzzy logic in population projections: the case of Mexico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Argote-Cusi]]></surname>
<given-names><![CDATA[Milenka Linneth]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad EAN  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2018</year>
</pub-date>
<volume>24</volume>
<numero>95</numero>
<fpage>273</fpage>
<lpage>301</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-74252018000100273&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-74252018000100273&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-74252018000100273&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: La presente investigación se enmarca en los estudios de optimización en busca de mejores estimaciones. Esta propuesta considera una nueva forma de proyectar los datos poblacionales de México tomando como referente la teoría de los conjuntos difusos, que a través de funciones de membrecía borrosas permite modelar la variable lingüística &#8220;Crecimiento poblacional&#8221; considerando las características no lineales del sistema. Se utilizó la serie de datos de población total de México desde 1895 a 2010 producto de censos y conteos realizados por el Instituto Nacional de Estadística y Geografía del país. Se retoman las definiciones y teoremas de las series de tiempo difusas que emergen de la teoría de conjuntos difusos desarrollados por Zadeh (1965); en este caso se aplicó series de tiempo difusas invariantes en el tiempo. Se evidencia que la proyección de datos poblacionales utilizando series de tiempo difusas resulta ser un método que logra captar la no linealidad del comportamiento poblacional, se logra proyectar con pocos datos históricos y se reduce el error en comparación con una regresión lineal simple.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The main topic of this research is the new methods to improve the accuracy of population estimations. Considering fuzzy logic theory trough membership function, we project Mexican population, phenomenon who has no lineal dynamic. Population series from census and counts between 1895 and 2010 was used join definitions and theorems of fuzzy time series developed by Zadeh (1965); in this case was apply fuzzy time series invariant in time. Fuzzy times series forecasting achieves to model no lineal behavior of population with few data and we see that the error of these new estimations is smaller than simple linear regression.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Proyecciones de población con lógica borrosa]]></kwd>
<kwd lng="es"><![CDATA[series de tiempo borrosas]]></kwd>
<kwd lng="es"><![CDATA[análisis de precisión de las estimaciones]]></kwd>
<kwd lng="en"><![CDATA[Fuzzy logic population projection]]></kwd>
<kwd lng="en"><![CDATA[Fuzzy Time Series for forecasting]]></kwd>
<kwd lng="en"><![CDATA[Accuracy Estimates Analysis]]></kwd>
</kwd-group>
</article-meta>
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