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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">tinro</journal-id><journal-title-group><journal-title xml:lang="ru">Известия ТИНРО</journal-title><trans-title-group xml:lang="en"><trans-title>Izvestiya TINRO</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1606-9919</issn><issn pub-type="epub">2658-5510</issn><publisher><publisher-name>ТИНРО</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26428/1606-9919-2022-202-1002-1014</article-id><article-id custom-type="elpub" pub-id-type="custom">tinro-795</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>МЕТОДИКА ИССЛЕДОВАНИЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>METHODS OF INVESTIGATIONS</subject></subj-group></article-categories><title-group><article-title>Применение метода машинного обучения для оценки биомассы трески в Северо-Курильской зоне</article-title><trans-title-group xml:lang="en"><trans-title>Application of the machine learning method to estimate the biomass of pacific cod in the North Kuril zone</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0920-5312</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кулик</surname><given-names>В. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Kulik</surname><given-names>V. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кулик Владимир Владимирович, кандидат биологических наук, заведующий лабораторией</p><p>690091, г. Владивосток, пер. Шевченко, 4</p></bio><bio xml:lang="en"><p>Vladimir V. Kulik - Ph.D., head of laboratory</p><p>690091, Vladivostok, Shevchenko Alley, 4</p></bio><email xlink:type="simple">vladimir.kulik@tinro-center.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>Горюнов</surname><given-names>М. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Goryunov</surname><given-names>M. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Горюнов Михаил Игоревич, ведущий специалист</p><p>690091, г. Владивосток, пер. Шевченко, 4</p></bio><bio xml:lang="en"><p>Mikhail I. Goryunov - leading specialist</p><p>690091, Vladivostok, Shevchenko Alley, 4</p></bio><email xlink:type="simple">mikhail.goryunov@tinro-center.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Тихоокеанский филиал ВНИРО (ТИНРО)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Pacific branch of VNIRO (TINRO)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>03</day><month>01</month><year>2023</year></pub-date><volume>202</volume><issue>4</issue><fpage>1002</fpage><lpage>1014</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Кулик В.В., Горюнов М.И., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Кулик В.В., Горюнов М.И.</copyright-holder><copyright-holder xml:lang="en">Kulik V.V., Goryunov M.I.</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://izvestiya.tinro-center.ru/jour/article/view/795">https://izvestiya.tinro-center.ru/jour/article/view/795</self-uri><abstract><p>Исследуются уловы тихоокеанской трески Gadus macrocephalus на промысле и в научной съемке с целью найти относительную биомассу трески и ее неопределенность в Северо-Курильской зоне в 2021 и 2022 гг. с использованием многофакторного подхода. Используется вся доступная в ТИНРО информация за эти годы для проведения сравнительного анализа посредством метода машинного обучения — ансамблевого метода случайного леса (Random forest) в процедуре множественного заполнения пропусков последовательными уравнениями — Multiple Imputation by Chained Equations (MICE). Коэффициент детерминации относительно тестовых данных превышал 0,8 при использовании данных научной съемки 2021 г., а при использовании промысловых данных он превышал 0,5. Тем не менее относительно исходной дисперсии: таковая в MICE была ниже более чем на 82 % по данным научной съемки. Выявлено, что биомасса трески осталась на прежнем уровне в 2022 г. относительно 2021 г. Предлагается расширить район исследований и список наблюдаемых орудий лова из-за их пространственной сегрегации для снижения вероятности искажения оценок в связи с большой площадью экстраполяции.</p></abstract><trans-abstract xml:lang="en"><p>The biomass of pacific cod (Gadus macrocephalus) in the North Kuril fishing zone is estimated using a multifactorial approach, with evaluation of uncertainty. For this purpose, the density of fish over entire zone is restored using the data on density obtained in 2022 compared with the data of previous surveys and fishery data obtained in 2021 and earlier, converted to the same scale, with application of the machine learning method, as the random forest in the multiple imputation by chained equations procedure (MICE). The coefficient of the restored data determination with out-of-bag (test set) data was &gt; 0.8 with the data of scientific survey in 2021 and &gt; 0.5 with the data of Danish seine observations. The cod density variance in MICE data was in 82 % lower than in the data of the scientific survey; therefore the biomass estimation with MICE data has lower uncertainty than that one calculated just from the mean density in survey. The study showed insignificant difference of the cod biomass in 2021 and 2022. Spatial segregation is revealed for fishing gears used for the pacific cod fishery. There is proposed to extend the list of fishing gears and to expand the study area for reducing possible bias in the biomass estimation due to large area of extrapolation.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>биомасса</kwd><kwd>тихоокеанская треска</kwd><kwd>Северо-Курильская зона</kwd><kwd>случайный лес</kwd><kwd>MICE</kwd></kwd-group><kwd-group xml:lang="en"><kwd>biomass</kwd><kwd>pacific cod</kwd><kwd>North Kuril fishing zone</kwd><kwd>random forest</kwd><kwd>MICE</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Авторы выражают признательность всем участникам научных рейсов и наблюдателям на промысле, чьи материалы использованы для настройки моделей. Отдельная благодарность сотрудникам Центра системы мониторинга рыболовства и связи (ЦСМС) и Института космических исследований РАН (ИКИ РАН) за ведение базы данных ОСМ и предоставление доступа к ним. Материалы собраны и обработаны по договору на выполнение научно-исследовательских работ № 40–22 с АО «СК БСФ» от 13 апреля 2022 г.</funding-statement><funding-statement xml:lang="en">The authors are thankful to all members of scientific cruises and observers whose materials were used to adjust the models. Special thanks to the staff of the Center for Fisheries Monitoring System and Communications and the Space Research Institute of the Russian Academy of Sciences (IKI RAS) for maintaining the OSM database and providing access to them. The materials for the study were collected and processed under the contract for the performance of research work No. 40-22 with JSC «IC BSF» dated April 13, 2022.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Аксютина З.М. Количественная оценка скопления рыб методом изолиний // Тр. 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