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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">techtransp</journal-id><journal-title-group><journal-title xml:lang="ru">Техник транспорта: образование и практика</journal-title><trans-title-group xml:lang="en"><trans-title>Transport Technician: Education and Practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2687-1025</issn><issn pub-type="epub">2687-1033</issn><publisher><publisher-name>Federal state budget establishment additional professional education «Educational and instructional center for railway transportation»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.46684/2687-1033.2020.3.216-220</article-id><article-id custom-type="elpub" pub-id-type="custom">techtransp-121</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>ТЕХНИКА И ТЕХНОЛОГИЯ ОРГАНИЗАЦИИ ПЕРЕВОЗОК. ТЕХНОСФЕРНАЯ БЕЗОПАСНОСТЬ НА ТРАНСПОРТЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>METHODS AND TECHNOLOGY OF TRANSPORT MANAGEMENT. TECHNOSPHERIC SECURITY IN TRANSPORT</subject></subj-group></article-categories><title-group><article-title>Исследование алгоритма прогноза оценки опасности электрокоррозии в обделках железнодорожных тоннелей</article-title><trans-title-group xml:lang="en"><trans-title>Investigation of the forecast algorithm for assessing the risk of electrocorrosion in the lining of railway tunnels</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>Мен Чжин</surname><given-names>Чу</given-names></name><name name-style="western" xml:lang="en"><surname>Myong Jin</surname><given-names>Ju</given-names></name></name-alternatives><bio xml:lang="ru"><p>Чу Мен Чжин — Ph.D., преподаватель кафедры тяговой электроэнергии электротехнического факультета</p><p>г. Пхеньян, КНДР, Хенчжесанский район, Хадан-1</p></bio><bio xml:lang="en"><p>Ju Myong Jin — Ph.D., lecturer of the Department of Traction Electricity of the Electrical Engineering Faculty</p><p>Pyongyang, DPRK, Henjesan region, Hadan-1</p></bio><email xlink:type="simple">ttspo@umczdt.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>Ким Гвон</surname><given-names>Ким</given-names></name><name name-style="western" xml:lang="en"><surname>Kim Gwon</surname><given-names>Kim</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ким Гвон — Ph.D., преподаватель кафедры тяговой электроэнергии электротехнического факультета</p><p>г. Пхеньян, КНДР, Хенчжесанский район, Хадан-1</p></bio><bio xml:lang="en"><p>Kim Gwon — Ph.D., lecturer of the Department of Traction Electricity of the Electrical Engineering Faculty</p><p>Pyongyang, DPRK, Henjesan region, Hadan-1</p></bio><email xlink:type="simple">ttspo@umczdt.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Пхеньянский институт путей сообщения</institution><country>Северная Корея</country></aff><aff xml:lang="en"><institution>Pyongyang University of Railway Engineering</institution><country>Korea, Democratic People's Republic of</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>21</day><month>08</month><year>2020</year></pub-date><volume>1</volume><issue>3</issue><fpage>216</fpage><lpage>220</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Мен Чжин Ч., Ким Гвон К., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Мен Чжин Ч., Ким Гвон К.</copyright-holder><copyright-holder xml:lang="en">Myong Jin J., Kim Gwon K.</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://www.ttspo.ru/jour/article/view/121">https://www.ttspo.ru/jour/article/view/121</self-uri><abstract><p>В железнодорожных тоннелях арматура несущих конструкций, внутренние металлические конструкции и оборудование в наибольшей степени подвержены электрокоррозии, в отличие от других подобных конструкций, расположенных за пределами тоннеля. Это связано прежде всего с большим количеством влаги, накопленным в верхнем строении пути. По результатам анализа можно сделать вывод, что в среднем сроки службы конструкций внутри тоннелей ниже (в среднем на 40–50 %), чем за его пределами</p></abstract><trans-abstract xml:lang="en"><p>Railway tunnels are more damaged by electrical corrosion from local conditions than other objects, since they contain a lot of moisture and emissions accumulated between the railway track and the rails. The analysis shows that the average service life of structures inside tunnels is shorter (on average by 40–50 %) than outside tunnels. A variant of intelligent systems for predicting electrocorrosion of tunnel structures is presented, a VR-neural network is applied to it, the advantages of which are currently recognized in different areas, including in the field of intelligent control. The study is devoted to an algorithm using a neural network of the backpropagation method to develop a system for assessing the risk of electrocorrosion in the lining of a railway tunnel</p></trans-abstract><kwd-group xml:lang="ru"><kwd>электрокоррозия</kwd><kwd>нейронная сеть</kwd><kwd>железнодорожный туннель</kwd></kwd-group><kwd-group xml:lang="en"><kwd>electric corrosion</kwd><kwd>neuron network</kwd><kwd>railway tunnel</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">C.S.Chan, L.F.Tian. Worst-case identification of touch voltage and stray current of DC railway system using genetic algorithm. IEE Proceeding ; Electric Power Application 146 5 2004 IEEp 570~576</mixed-citation><mixed-citation xml:lang="en">C.S.Chan, L.F.Tian. Worst-case identification of touch voltage and stray current of DC railway system using genetic algorithm. 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