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<article article-type="research-article" dtd-version="1.3" 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" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">ipolytech</journal-id><journal-title-group><journal-title xml:lang="ru">iPolytech Journal</journal-title><trans-title-group xml:lang="en"><trans-title>iPolytech Journal</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2782-4004</issn><issn pub-type="epub">2782-6341</issn><publisher><publisher-name>Irkutsk National Research Technical University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21285/1814-3520-2018-8-72-82</article-id><article-id custom-type="elpub" pub-id-type="custom">ipolytech-151</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ИНФОРМАТИКА, ВЫЧИСЛИТЕЛЬНАЯ ТЕХНИКА И УПРАВЛЕНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFORMATION SCIENCE, COMPUTER ENGINEERING AND CONTROL</subject></subj-group></article-categories><title-group><article-title>МЕТОД СОПРЯЖЕННЫХ ГРАДИЕНТОВ В СИСТЕМЕ АВТОМАТИЧЕСКОГО ПОСТРОЕНИЯ ПРОГНОЗИРУЮЩИХ МОДЕЛЕЙ</article-title><trans-title-group xml:lang="en"><trans-title></trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Серышева</surname><given-names>И. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Serysheva</surname><given-names>I. A.</given-names></name></name-alternatives><email xlink:type="simple">sia_cyber@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чекан</surname><given-names>М. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Chekan</surname><given-names>M. A.</given-names></name></name-alternatives><email xlink:type="simple">chekoopa@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бархатова</surname><given-names>Л. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Barkhatova</surname><given-names>L. V.</given-names></name></name-alternatives><email xlink:type="simple">lyuda_barhatova@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Крупенев</surname><given-names>Е. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Krupenev</surname><given-names>E. A.</given-names></name></name-alternatives><email xlink:type="simple">egorkrupenev@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Иркутский национальный исследовательский технический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Irkutsk National Research Technical University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2018</year></pub-date><pub-date pub-type="epub"><day>15</day><month>09</month><year>2020</year></pub-date><volume>22</volume><issue>8</issue><fpage>72</fpage><lpage>82</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Серышева И.А., Чекан М.А., Бархатова Л.В., Крупенев Е.А., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Серышева И.А., Чекан М.А., Бархатова Л.В., Крупенев Е.А.</copyright-holder><copyright-holder xml:lang="en">Serysheva I.A., Chekan M.A., Barkhatova L.V., Krupenev E.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://ipolytech.elpub.ru/jour/article/view/151">https://ipolytech.elpub.ru/jour/article/view/151</self-uri><trans-abstract xml:lang="en"><p>PURPOSE. The paper deals with the increase in reproduction accuracy of time and frequency units through the use of predictive autoregressive-moving average models (ARMA)). The methodology of ARMA model creation existing now is based on interactive procedures. This requires highly qualified specialists and prevents the algorithms of optimum filtration from the introduction in the practical activities of time services. METHODS. The study employs the methods of time series analysis, ARMA model construction and the conjugate gradients method. RESULTS. An approach allowing a complete formalization of the procedure of model construction is introduced. A program module implementing the automatic construction of the predicting models that describe the processes of hydrogen standards frequency variation is developed. It is tested experimentally and the results of the work confirming the adequacy of the obtained models are presented. CONCLUSIONS. The formalized methodology of ARMA models construction proposed by the authors will allow to solve the problem of full automation of time series model construction by empirical data and to lower the reproduction error of time and frequency units by group standards up to 30%.The conducted study provides all the reasons to suppose that the developed software module can serve as a basis for creating a standard software for the subsystem of internal comparisons of time and frequency standards in order to be introduced into the experimental operation mode.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>predictive models of time series</kwd><kwd>search for unconditional extremum</kwd><kwd>method of conjugate gradients</kwd><kwd>adequacy of predicting models</kwd><kwd>group time and frequency standards</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Panfilo G., Harmegnies A., Tisserand L.A new prediction algorithm for the generation of International Atomic Time // Metrologia. 2012. 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