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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xml:lang="ru">
  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>Computing, Telecommunication and Control</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Информатика, телекоммуникации и управление</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2687-0517</issn>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">23</article-id>
      <title-group>
        <article-title>Neural networks approach to the solution of incorrect heat transfer problems</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Нейросетевой подход к решению некорректных задач теплопереноса</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Vasiliev</surname>
            <given-names>Alexander</given-names>
          </name>
          <email>a.n.vasilycv@gmail.com</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Porubayev</surname>
            <given-names>Filipp</given-names>
          </name>
          <email>porphill@mail.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Tarkhov</surname>
            <given-names>Dmitry</given-names>
          </name>
          <email>dtarkhov@gmail.com</email>
        </contrib>
      </contrib-group>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2011-02-10">
        <day>10</day>
        <month>02</month>
        <year>2011</year>
      </pub-date>
      <issue>1</issue>
      <issue-id pub-id-type="publisher-id">115</issue-id>
      <fpage>133</fpage>
      <lpage>142</lpage>
      <abstract xml:lang="en">
        <p>An approach to the solution of incorrect problem of temperature field evaluation according to approximately known point measurement data is offered on the basis of neural network methodology. Results of neurocomputing are given. Advantages of neural network approach and some possible generalizations are mentioned.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>partial differential equations</kwd>
        <kwd>incorrect problems</kwd>
        <kwd>neural network model</kwd>
        <kwd>artificial neural network training</kwd>
        <kwd>error functional</kwd>
        <kwd>global optimization</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
