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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="en">
  <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">21</article-id>
      <title-group>
        <article-title>Neuronet operating by locomotion system of self-training bio-object model moving to target</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Нейросетевое управление локомоциями самообучающейся модели биообъекта</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Poptsov</surname>
            <given-names>Nikolay</given-names>
          </name>
          <email>Nikolai_work@mail.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bekurin</surname>
            <given-names>Dmitry</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2009-10-10">
        <day>10</day>
        <month>10</month>
        <year>2009</year>
      </pub-date>
      <issue>5</issue>
      <issue-id pub-id-type="publisher-id">86</issue-id>
      <fpage>119</fpage>
      <lpage>122</lpage>
      <abstract xml:lang="en">
        <p>Self-training of bio-object (amoeba) locomotion system model which is operating by neuronet is considered. Amoeba model was prototyped by two ellipsoids connected with each other by thin channel. The length of the channel and the forms of ellipsoids are controlled by operating system. The motions of the model in the fluid are considered in Stocks approximation. Two scenarios of self-training are considered and their effectiveness are compared for different distances from target and initial object orientation angles.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>self-training neuronet</kwd>
        <kwd>model of locomotion system</kwd>
        <kwd>amoeba swimming modelling</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
