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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">ntv</journal-id><journal-title-group><journal-title xml:lang="ru">Научно-технический вестник информационных технологий, механики и оптики</journal-title><trans-title-group xml:lang="en"><trans-title>Scientific and Technical Journal of Information Technologies, Mechanics and Optics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2226-1494</issn><issn pub-type="epub">2500-0373</issn><publisher><publisher-name>Университет ИТМО</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17586/2226-1494-2025-25-1-151-159</article-id><article-id custom-type="elpub" pub-id-type="custom">ntv-430</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>МАТЕМАТИЧЕСКОЕ И КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MODELING AND SIMULATION</subject></subj-group></article-categories><title-group><article-title>Подход к решению проблемы дефицита геомагнитных данных  в задачах поддержки принятия решений</article-title><trans-title-group xml:lang="en"><trans-title>An approach to solving the problem of geomagnetic data scarcity in decision-making support</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7878-9724</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Воробьева</surname><given-names>Г. Р.</given-names></name><name name-style="western" xml:lang="en"><surname>Vorobeva</surname><given-names>G. R.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Воробьева Гульнара Равилевна — доктор технических наук, доцент, профессор</p><p>Уфа, 450008</p></bio><bio xml:lang="en"><p>Gulnara R. Vorobeva — D.Sc., Associate Professor, Professor</p><p>Ufa, 450008</p></bio><email xlink:type="simple">gulnara.vorobeva@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9680-5609</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Воробьев</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Vorobev</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Воробьев Андрей Владимирович — доктор технических наук, доцент, профессор, заведующий кафедрой</p><p>Уфа, 450008</p></bio><bio xml:lang="en"><p>Andrei V. Vorobev — D.Sc., Associate Professor, Professor, Head of Department</p><p>Ufa, 450008</p></bio><email xlink:type="simple">geomagnet@list.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0001-4107-8950</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Фарваев</surname><given-names>Э. Ф.</given-names></name><name name-style="western" xml:lang="en"><surname>Farvaev</surname><given-names>E. F.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Фарваев Эмиль Фанильевич — аспирант</p><p>Уфа, 450008</p></bio><bio xml:lang="en"><p>Emil F. Farvaev — PhD Student</p><p>Ufa, 450008</p></bio><email xlink:type="simple">farvaev.emil@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Уфимский университет науки и технологий</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Ufa University of Science and Technology</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>28</day><month>02</month><year>2025</year></pub-date><volume>25</volume><issue>1</issue><fpage>151</fpage><lpage>159</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Воробьева Г.Р., Воробьев А.В., Фарваев Э.Ф., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Воробьева Г.Р., Воробьев А.В., Фарваев Э.Ф.</copyright-holder><copyright-holder xml:lang="en">Vorobeva G.R., Vorobev A.V., Farvaev E.F.</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://ntv.elpub.ru/jour/article/view/430">https://ntv.elpub.ru/jour/article/view/430</self-uri><abstract><p>Введение. Одной из главных проблем применения данных в задачах поддержки принятия решений является их дефицит в определенных пространственных точках/областях ввиду невозможности проведения соответствующих измерений. Примером этого являются данные о состоянии магнитного поля Земли (геомагнитные данные), на основании которых принимаются решения для сокращения негативного воздействия экстремальных геофизических событий на объекты и системы техносферы (линии электропередач, системы связи, автоматика железных дорог и пр.). Анализ существующей инфраструктуры сбора геомагнитных данных с позиций системного анализа позволил идентифицировать неполное покрытие сетью мониторинга, что негативно сказывается на принятии решений при обеспечении техносферной безопасности в пространственных областях. На примере геомагнитных данных выявлено, что известные методы интерполяции, не учитывающие особенности пространственно-временных характеристик описываемых данными процессов и их зависимость от внешних факторов, недостаточно эффективно справляются с поставленной задачей. Метод. Для решения обозначенной проблемы предложен подход к адаптивной пространственной интерполяции, основной идеей которого является динамический подбор методов интерполяции, наиболее эффективных при различных факторах. Для примера геомагнитных данных в качестве таких факторов выбраны принадлежность пространственной точки определенной широтной зоне и индекс геомагнитной активности в рассматриваемый период времени. Основные результаты. Для оценки предлагаемого решения разработан прототип веб-ориентированного приложения. Эксперимент проведен с использованием геомагнитной информации проекта SuperMAG. При сравнении среднеквадратической ошибки интерполяции применение предлагаемого подхода показало большую эффективность, чем применение какого-либо отдельного метода интерполяции. Обсуждение. Предложенная адаптивная интерполяция может быть использована в системах, реализующих интерполяцию геопространственных данных, как альтернатива стандартным методам интерполяции, с целью повышения точности восстановления данных. Сделан вывод, что при работе с геомагнитными данными могут быть использованы данные о широтной зоне и геомагнитной активности. Интерполяция данных иной природы может потребовать предварительного анализа для выявления значимых факторов.</p></abstract><trans-abstract xml:lang="en"><p>One of the main problems of using data in decision-making support is their scarcity in certain spatial points/areas due to the inability to carry out appropriate measurements. An example is the Earth’s magnetic field data (geomagnetic data) which is used to make decisions to reduce the extreme geophysical events negative impact on objects and systems of the technosphere (power lines, communication systems, railway automation, etc.). An analysis of the existing geomagnetic data collection infrastructure from the standpoint of system analysis made it possible to identify incomplete coverage of the monitoring network, which negatively affects decision-making to ensure technosphere security in the relevant spatial areas. Using the example of geomagnetic data, it was revealed that the known interpolation methods, which do not take into account the features of the spatiotemporal characteristics of the processes described by the data and their dependence on external factors, do not deal effectively with the task. To solve this problem, an approach to adaptive spatial interpolation is proposed the main idea of which is the dynamic selection of interpolation methods that are most effective for various factors. For an example of geomagnetic data two factors were chosen: the affiliation of a spatial point to a certain latitude zone and the index of geomagnetic activity in the time period under consideration. To evaluate the proposed solution, a prototype of a web-based application was developed. The experiment was conducted using geomagnetic information from the SuperMAG project. The proposed approach has proved to be more effective than using any separate interpolation method when comparing the root-mean-square errors. Adaptive interpolation proposed in this paper can be used in systems implementing interpolation of geospatial data, as an alternative to standard interpolation methods, in order to increase the accuracy of data recovery. When working with geomagnetic data, the factors considered in this work (latitudinal zones and geomagnetic activity) can be used, but interpolation of data of a different nature will require preliminary analysis to identify significant factors.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>геопространственные данные</kwd><kwd>геомагнитные данные</kwd><kwd>системный анализ</kwd><kwd>пространственная интерполяция</kwd><kwd>поддержка принятия решений</kwd><kwd>веб-приложения</kwd></kwd-group><kwd-group xml:lang="en"><kwd>geospatial data</kwd><kwd>geomagnetic data</kwd><kwd>system analysis</kwd><kwd>spatial interpolation</kwd><kwd>decision support</kwd><kwd>web applications</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено за счет гранта Российского научного фонда № 25-21-00143, https://rscf.ru/project/25-21-00143/.</funding-statement><funding-statement xml:lang="en">The study was carried out with the financial support of the Russian Science Foundation, project No. 25-21-00143,  https://rscf.ru/project/25-21-00143/.</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">Vorobev A., Soloviev A., Pilipenko V., Vorobeva G., Sakharov Y. 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