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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">100106</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.2012.10(1).1029
</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Use of Generalized Maximum Entropy Estimation for Freight Flows Modelling and an Application</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Satici</surname>
            <given-names>Esra</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">General Directorate of Turkish Highways</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Demirhan</surname>
            <given-names>Haydar</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Hacettepe University</aff>
      </contrib-group>
      <volume>10</volume>
      <issue>1</issue>
      <fpage>75</fpage>
      <lpage>86</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: In this paper, freight transportation is taken into account. One of the models used for modelling “Origin-Destination” freight flows is log regression model obtained by applying a log-transformation to the tradi tional gravity model. Freight flows between ten provinces of Turkey is ana lyzed by using generalized maximum entropy estimator of the log-regression model for freight flow. The data set is gathered together from the axle load survey performed by Turkish Directorate of Highways and other so cioeconomic and demographic variables related with provinces of interest. Relations between considered socioeconomic and demographic variables and freight flows are figured out and results are discussed.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Bootstrap method</kwd>
        <kwd>freight demand modelling</kwd>
        <kwd>gravity model</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
